Cross-layer wireless multimedia transmission: challenges, principles, and new paradigms

Wireless networks are poised to enable a variety of existing and emerging multimedia streaming applications. As the use of wireless local area networks spreads beyond simple data transfer to bandwidth-intense, delay-sensitive, and loss-tolerant multimedia applications, addressing quality of service issues become extremely important. Currently, a multitude of protection and adaptation strategies exists in the different layers of the open systems interconnection (OSI) stack. Hence, an in-depth understanding and comparative evaluation of these strategies are necessary to effectively assess and enable the possible trade-offs in multimedia quality, power consumption, implementation complexity, and spectrum utilization that are provided by the various OSI layers. This further opens the question of cross-layer optimization and its effectiveness in providing an improved solution with respect to the above trade-offs. In this article we formalize the cross-layer problem, discuss its challenges, and present several possible solutions. Moreover, we also discuss the impact the cross-layer optimization strategy deployed at one station has on the multimedia performance of other stations. We introduce a new fairness concept for wireless multimedia systems that employs different cross-layer strategies, and show its advantages when compared to existing resource allocation mechanisms used in wireline communications. Finally, we propose a new paradigm for wireless communications based on competition, which allows wireless stations to harvest additional resources or free up resources as well as optimally and dynamically adapt their cross-layer transmission strategies to improve multimedia quality and/or power consumption.     

Radio resource management in future wireless networks: requirementsand limitations

Comparing market estimates for wireless personal communication and considering proposals for wideband multimedia services with the existing spectrum allocations for these types of systems show that spectrum resource management remains an important topic in the near and distant future. In this article the authors start by presenting a quite general formulation of the radio resource management problem where the three key allocation decisions are concerned with waveforms (“channels”), access ports (or base stations), and, finally, with transmitter power. Some approaches to these problems found in the literature are reviewed. In particular, the principles of random channel allocation schemes, as found in frequency-hopping or direct-sequence CDMA systems, are compared with deterministic dynamic channel allocation schemes. The article closes by giving an outlook of some of the key problems in resource management in future wireless multimedia systems     

Resource allocation in cellular networks based on marketing preferences

As the usage of cellular phones increases wireless subscribers demand many advanced networking capabilities, especially multimedia applications with very high Quality of Service (QoS) requirements. The limited availability of radio spectrum enforces Mobile Network Operators (MNOs) to have efficient resource management strategies. The goal is to offer services that satisfy the QoS requirements of individual users while achieving an efficient utilization of network resources. This paper considers a resource allocation strategy for cellular networks to be applied during call initiation, handoff and allocation of mobile base stations. Long-term customer retention becomes a major challenge for MNOs due to severe competition in the telecommunications industry. Therefore the MNOs need to understand the customer demographics as well as the customer spending behavior in telecommunications market. Our proposed model combines the information about the customer demographics and usage behavior once the call is initiated. Our hypothesis is that using customer information together with call information yields an efficient customer-oriented resource management strategy. We have performed simulations with different real-life scenarios. Our results show that our proposed model performs better in terms of revenue increase when compared to the First-Come First-Serve based approach.     

认知小蜂窝网络中基于能效的下行资源分配算法

在认知小蜂窝网络框架下,对基于OFDMA技术的下行联合频谱资源块和功率分配问题进行了研究。小蜂窝基站在分布式结构下采用开放式接入方式共享空闲频谱资源以最大化其能量效率,基站间的竞争关系使系统资源的动态分配过程可建模为非合作博弈模型。由于最大化具有多个限制条件的分数形势的能量效用函数属于非凸最优问题,可通过将其转化为等价的减数形势,并从串行和并行迭代的角度进行求解。在给定资源块分配策略后,原有博弈模型可被重新建模为便于独立求解发射功率的等价子博弈模型。仿真结果表明,所提算法在干扰受限的通信环境下能收敛到纳什均衡,并有效提高了系统资源利用率和能量效率。     

Spectrum allocation for wireless backhaul in heterogeneous ultra-dense networks

Wireless ultra-dense network (UDN) is one of the important technologies to solve the burst of throughput demand in the forthcoming fifth generation (5G) cellular networks. Reusing spectrum resource for the backhaul of small base stations (SBSs) is a hotspot research because of lower cost and rapid implementation with macro base stations (MBSs) in recent years. In heterogeneous UDN, the problem of spectrum allocation for wireless backhaul is investigated. In particular, two different spectrum resource reusing strategies for wireless backhaul are proposed in heterogeneous UDN with the limited bandwidth condition. Using a stochastic geometry-based heterogeneous UDN model, the success probabilities that mobile users communicate with SBSs or MBSs are derived under two different spectrum resource reusing strategies. In addition, the network throughput’s analytical expressions and the optimal ratio of spectrum allocation are derived. Numeral results are provided to evaluate the performance of the proposed strategies at throughput. Thus, the effectiveness of the strategy that mobile users can only communicate with SBSs is validated.     

Stackelberg game for backhaul resource allocation in the two-tier LTE femtocell networks

As one promising technology for indoor coverage and service offloading from the conventional cellular networks, femtocells have attracted considerable attention in recent years. However, most of previous work are focused on resource allocation during the access period, and the backhaul involved resource allocation is seriously ignored. The authors studied the backhaul resource allocation in the wireless backhaul based two-tier heterogeneous networks （HetNets）, in which cross-tier interference control during access period is jointly considered. Assuming that the macrocell base station （MBS） protects itself from interference by pricing the backhaul spectrum allocated to femtocells, a Stackelberg game is formulated to work on the joint utility maximization of the macrocell and femtocells subject to a maximum interference tolerance at the MBS. The closed-form expressions of the optimal strategies are obtained to characterize the Stackelberg equilibriums for the proposed games, and a backhaul spectrum payment selection algorithm with guaranteed convergence is proposed to implement the backhaul resource allocation for femtocell base stations （FBSs）. Simulations are presented to demonstrate the Stackelberg equilibrium （SE） is obtained by the proposed algorithm and the proposed scheme is effective in backhaul resource allocation and macrocell protection in the spectrum-sharing HetNets.     

Multimedia Service Discrimination Based on Fair Resource Allocation Using Bargaining Solutions

We deal with a resource allocation problem for multimedia service discrimination in wireless networks. We assume that a service provider allocates network resources to users who can choose and access one of the discriminated services. To express the rational service selection of users, the utility function of users is devised to reflect both service quality and cost. Regarding the utility function of a service provider, total profit and efficiency of resource usage have been considered. The proposed service discrimination framework is composed of two game models. An outer model is a repeated Stackelberg game between a service provider and a user group, while an inner model is a service selection game among users, which is solved by adopting the Kalai‐Smorodinsky bargaining solution. Through simulation experiments, we compare the proposed framework with existing resource allocation methods according to user cost sensitivity. The proposed framework performed better than existing frameworks in terms of total profit and fairness.     

对策论方法在信息网络资源分配中的应用

在研究复杂信息网络的资源分配问题时,网络资源提供者和用户之间对资源的使用存在不同的优化目标,导致对资源分配策略存在多种评价准则。为便于网络管理者进行分布式的资源管理和计费,采用对策论模型分析用户对资源的竞争和处理网络传输拥塞正日益受到广泛的重视。本文首先指出资源分配和计费管理的几个主要难点,比较了中心化与非中心化控制策略的差别,而后综述了采用对策论模型进行资源分配和管理的优点,重点讨论了在非中心化条件下对策均衡解与资源利用效率以及网络计费管理策略之间的关系,最后对基于对策论模型的信息网络流量控制与管理策略进行总体评述。     

面向分布式缓存系统的无线资源管理:动机、挑战与方法

移动社交网络平台的多元化发展与推广,使得移动用户对数据传输的需求呈爆发式增长趋势,并对匮乏的频谱资源及高负荷基站的管理提出了新挑战.为了解决这些问题,将分布式缓存系统引入无线协作网络中,鼓励移动用户间协作缓存热门内容,以实现用户间低能耗、高可靠、低时延的内容共享,同时为基站和回程链路减负.分析了无线分布式缓存系统中无线资源管理所面临的机遇和挑战,针对频谱高效、能量高效及安全传输等关键问题,围绕图论和匹配理论对无线资源管理方法展开了讨论和总结.此外,讨论和分析了挖掘和利用社交信息有效提升无线资源效率的可行性,同时对社会学和无线网络领域的交叉研究进行了展望.     

Guest Editorial - Adaptive, spectrum agile and cognitive wireless networks

The 11 papers in this special issue focus on adaptive, spectrum agile and cognitive wireless networks. Some of the topics covered include: fundamental performance aspects of spectrum sharing; spectrum sensing capabilities in cognitive radios; detection and estimation approaches to spectrum sharing; MAC design in opportunistic spectrum access; and competitive spectrum sharing and resource allocation using concepts from game theory and pricing.     

Collaborative resource exchanges for peer-to-peer video streaming over wireless mesh networks

Peer-to-peer collaboration paradigms fundamentally change the passive way wireless stations currently adapt their transmission strategies to match available resources, by enabling them to proactively influence system dynamics through exchange of information and resources. In this paper, we focus on delay-sensitive multimedia transmission among multiple peers over wireless multi-hop enterprise mesh networks. We propose a distributed and efficient framework for resource exchanges that enables peers to collaboratively distribute available wireless resources among themselves based on their quality of service requirements, the underlying channel conditions, and network topology. The resource exchanges are enabled by the scalable coding of the video content and the design of cross-layer optimization strategies, which allow efficient adaptation to varying channel conditions and available resources. We compare our designed low complexity distributed resource exchange algorithms against an optimal centralized resource management scheme and show how their performance varies with the level of collaboration among the peers. We measure system utility in terms of the multimedia quality and show that collaborative approaches achieve ~50% improvement over non-collaborative approaches. Additionally, our distributed algorithms perform within 10% system utility of a centralized optimal resource management scheme. Finally, we observe 2-5 dB improvement in decoded PSNR for each peer due to the deployed cross-layer strategy     

Multi-Stage Pricing Game for Collusion-Resistant Dynamic Spectrum Allocation

In order to fully utilize scarce spectrum resources, dynamic spectrum allocation becomes a promising approach to increase the spectrum efficiency for wireless networks. However, the collusion among selfish network users may seriously deteriorate the efficiency of dynamic spectrum sharing. The network users' behaviors and dynamics need to be taken into consideration for efficient and robust spectrum allocation. In this paper, we model the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. In order to combat user collusion, we propose a pricing-based collusion-resistant dynamic spectrum allocation approach to optimize overall spectrum efficiency, while not only keeping the participating incentives of the selfish users but also combating possible user collusion. The simulation results show that the proposed scheme achieves high efficiency of spectrum usage even with the presence of severe user collusion.     

认知小蜂窝网络中基于干扰温度限制的下行能效资源分配算法

为最大化认知小蜂窝基站的能量效率,本文基于博弈论模型分析了下行联合频谱资源块和功率分配行为.在干扰受限环境下,多个基站采用分布式结构共享空闲频谱资源.为避免累加干扰损害主用户的通信,算法中引入了功率和干扰温度限制.由于具有耦合限制的分数形式的能量效用函数是非凸最优的,通过将其转化为等价的减数形式进行迭代求解.给定频谱资源块分配策略后,主博弈模型可被重新建模为便于求解发射功率的等价子博弈模型,并通过代价的形势解除耦合限制.仿真结果表明,本文所提算法能够收敛到纳什均衡,并有效提高了系统资源利用率和能量效率.     

Dynamic resource allocation tor multimedia services in mobilecommunication environments

As demand for networked multimedia applications is increasing rapidly, it is important to provide these services in mobile communication environments. In this paper, we identify system requirements for base stations in order to support multimedia services. These requirements include supporting concurrent connections for multiple users, allocation of resources dynamically to satisfy diverse resource requirements for multimedia applications, and reallocation of resources during handoff incurred by user movement or newly generated calls. These requirements can be used to design an interface between land-based and mobile environments to handle one of the most challenging issues in multimedia communication: enforcing interstream and intrastream synchronizations. We propose two quality of presentation (QOP) parameters for evaluating the quality of mobile multimedia connections, and analyze the validity of these requirements     

一种5G异构云无线接入网络的D2D资源分配算法

为了解决设备对设备(Device-to-Device,D2D)资源共享带来的信号干扰问题,提出了一种5G异构云无线接入网络的D2D通信资源分配算法.在保证服务质量的前提下,将宏用户设备的频谱资源分配给D2D和中继用户设备,并且把资源分配问题看作一对一的匹配博弈.采用婚姻匹配理论,得到初始的匹配方案.在初始匹配的基础上,提出了一种遵循卡尔多-希克斯(Kaldor-Hicks)原则的资源交换策略,以提高系统的吞吐量.仿真结果表明,该资源分配算法收敛较快,与现有方案相比,能使系统吞吐量提升15％以上,能给系统用户带来约10％的增益,并且有较强抗信道干扰能力.     

An efficient resource optimization scheme for D2D communication

With the rapid development of wireless technologies, wireless access networks have entered their Fifth-Generation (5G) system phase. The heterogeneous and complex nature of a 5G system, with its numerous technological scenarios, poses significant challenges to wireless resource management, making radio resource optimization an important aspect of Device-to-Device (D2D) communication in such systems. Cellular D2D communication can improve spectrum efficiency, increase system capacity, and reduce base station communication burdens by sharing authorized cell resources; however, can also cause serious interference. Therefore, research focusing on reducing this interference by optimizing the configuration of shared cellular resources has also grown in importance. This paper proposes a novel algorithm to address the problems of co-channel interference and energy efficiency optimization in a long-term evolution network. The proposed algorithm uses the fuzzy clustering method, which employs minimum outage probability to divide D2D users into several groups in order to improve system throughput and reduce interference between users. An efficient power control algorithm based on game theory is also proposed to optimize user transmission power within each group and thereby improve user energy efficiency. Simulation results show that these proposed algorithms can effectively improve system throughput, reduce co-channel interference, and enhance energy efficiency.     

Spectrum sharing method for secondary systems using frequency priority table to reduce inter-secondary interference

Because of the rapid development of cognitive radio technologies, research on sharing frequency resources allocated to primary users with secondary users has attracted much attention. If a frequency band is unused by the primary users, multiple secondary users are expected to share the spectrum in a future wireless communication network. To efficiently share the spectrum among secondary systems, we propose a novel channel allocation method that uses a frequency priority table generated based on the location of the secondary system. By using this method, the interference with other systems is autonomously reduced by selecting channels. Moreover, a power control method is also proposed for protecting the secondary systems that are allocated to the channels with higher priority.     

NOMA-MEC系统中基于改进遗传算法的协作式计算卸载与资源管理

为平衡网络负载与充分利用网络资源,针对超密集异构的多用户和多任务边缘计算网络,在用户时延约束下,该文构造了协作式计算任务卸载与无线资源管理的联合优化问题以最小化系统能耗。问题建模时,为应对基站超密集部署导致的严重干扰问题,该文采用了频带划分机制,并引入了非正交多址技术(NOMA)以提升上行频谱利用率。鉴于该目标优化问题具备非线性混合整数的形式,根据多样性引导变异的自适应遗传算法(AGADGM),设计出了协作式计算卸载与资源分配算法。仿真结果表明,在严格满足时延约束条件下,该算法能获取较其他算法更低的系统能耗。     

无线视频通信中带宽分配策略

本文针对无线网络中多用户传输视频时带宽分配问题,提出了一种基于微观经济学中供需平衡的带宽分配策略。该方法充分考虑了运营商的收益,在运营商和用户收益同时最大且供需平衡时,所求得的频谱价格即为运营商的出售价格。同时给出了针对不同用户等级有不同的用户优先级因子,据运营商提出的带宽价格,彼此相互博弈,最终使得自身效用最大。仿真结果表明:本文提出的博弈论方法存在纳什均衡解和均衡单价;用户等级因子能按照用户的不同等级来分配带宽;系统传输质量相比以往方法有所提高。      

一种基于无线多媒体业务的可升降级QoS动态带宽分配与优化策略

无线多媒体网络中的业务包括话音、流媒体、交互类和背景类业务4种,除话音业务外其余3种业务都是可变比特速率业务。对该网络用户资源分配(主要是带宽的分配)若采用传统的固定分配方法,必定陷入资源利用率低下和用户QoS得不到保障的两难境地。该文提出了一种基于无线多媒体业务的动态带宽分配与优化策略,在保证用户QoS的前提下,尽可能提高资源利用率。该文分别从网络和用户两个角度考虑,通过系统容量、业务阻塞率、数据延迟、流媒体的实际传输比和VBR业务综合服务等级等参数,对可升降级QoS无线多媒体网络进行了仿真分析,结果表明,对比传统的网络资源管理策略,该策略大大改善了系统的性能,提高了系统资源利用率。