Resource allocation for downlink multiuser video transmission over wireless lossy networks

Demand for multimedia services, such as video streaming over wireless networks, has grown dramatically in recent years. The downlink transmission of multiple video sequences to multiple users over a shared resource-limited wireless channel, however, is a daunting task. Among the many challenges in this area are the time-varying channel conditions, limited available resources, such as bandwidth and power, and the different transmission requirements of different video content. This work takes into account the time-varying nature of the wireless channels, as well as the importance of individual video packets, to develop a cross-layer resource allocation and packet scheduling scheme for multiuser video streaming over lossy wireless packet access networks. Assuming that accurate channel feedback is not available at the scheduler, random channel losses combined with complex error concealment at the receiver make it impossible for the scheduler to determine the actual distortion of the sequence at the receiver. Therefore, the objective of the optimization is to minimize the expected distortion of the received sequence, where the expectation is calculated at the scheduler with respect to the packet loss probability in the channel. The expected distortion is used to order the packets in the transmission queue of each user, and then gradients of the expected distortion are used to efficiently allocate resources across users. Simulations show that the proposed scheme performs significantly better than a conventional content-independent scheme for video transmission.     

Optimal resource allocation in multiservice CDMA networks

This paper addresses the problem of dynamic resource allocation in a multiservice direct-sequence code-division multiple-access (DS-CDMA) wireless network supporting real-time (RT) and nonreal-time (NRT) communication services. For RT users, a simple transmission power allocation strategy is assumed that maximizes the amount of capacity available to NRT users without violating quality of service requirements of RT users. For NRT users, a joint transmission power and spreading gain (transmission rate) allocation strategy, obtained via the solution of a constrained optimization problem, is provided. The solution maximizes the aggregate NRT throughput, subject to peak transmission power constraints and the capacity constraint imposed by RT users. The optimization problem is solved in a closed form, and the resulting resource allocation strategy is simple to implement as a hybrid CDMA/time-division multiple-access strategy. Numerical results are presented showing that the optimal resource allocation strategy can offer substantial performance gains over other conventional resource allocation strategies for DS-CDMA networks.     

Mechanism-based resource allocation for multimedia transmission over spectrum agile wireless networks

We propose to add a new dimension to existing wireless multimedia systems by enabling autonomous stations to dynamically compete for communication resources through adjustment of their internal strategies and sharing their private information. We focus on emerging spectrum agile wireless networks, where developing an efficient strategy for managing available communication resources is of high importance. The proposed dynamic resource management approach for wireless multimedia changes the passive way stations are currently adapting their joint source-channel coding strategies according to available wireless resources. Each wireless station can play the resource management game by adapting its multimedia transmission strategy depending on the experienced channel conditions and user requirements. The resource allocation game is coordinated by a network moderator, which deploys mechanism-based resource management to determine the amount of transmission time to be allocated to various users on different frequency bands such that certain global system metrics are optimized. Subsequently, the moderator charges the various users based on the amount of resources it has allocated to them, in order to discourage them from being dishonest about their resource requirements. We investigate and quantify both the users' and the system performance when different cross-layer strategies, and hence users' levels of smartness, are deployed by wireless stations. Our simulations show that mechanism-based resource management outperforms conventional techniques such as air-fair time and equal time resource allocation in terms of the obtained system utility. They also provide insights that can guide the design of emerging spectrum agile network protocols and applications     

Resource allocation based on cross-layer QoS-guaranteed scheduling for multi-service multi-user MIMO–OFDMA systems

Cross-layer strategies for resource allocation in wireless networks are essential to guaranty an efficient utilization of the scarce resource. In this paper, we present an efficient radio resource allocation scheme based on PHY/MAC cross layer design and QoS-guaranteed scheduling for multi-user (MU), multi-service (MS), multi-input multi-output (MIMO) concept, orthogonal frequency division multiple access (OFDMA) systems. It is about a downlink multimedia transmission chain in which the available resources as power and bandwidth, are dynamically allocated according to the system parameters. Among these parameters, we can mention the physical link elements such as channel state information, spectral efficiency and error code corrector rate, and MAC link variables, which correspond to the users QoS requirements and the queue status. Primarily, we use a jointly method which parametrizes these system parameters, according to the total power, and the bit error rate constraints. Secondly, we propose a QoS-guaranteed scheduling that shares the sub-carriers to the users. These users request several type of traffic under throughput threshold constraints. The main objective in this work is to adjust the average throughput per service of each user, according to their needs and likewise to satisfy a great number of connexions. Subsequently, we consider a model of moderated compartmentalization between various classes of services by partitioning the total bandwidth into several parts. Each class of service will occupy a part of the bandwidth and will be transmitted over a maximum number of sub-carriers. The simulation results show that the proposed strategy provides a more interesting performance improvement (in terms of average data rate and user satisfaction) than other existing resource allocation schemes, such as nonadaptive resource allocation strategy. The performances are also analyzed and compared for the two multi-service multi-user MIMO–OFDMA systems; with sub-carriers partitioning and without sub-carriers partitioning.     

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。     

A unified framework for distributed video rate allocation over wireless networks

When multiple video streams share a wireless network, careful rate allocation is needed to prevent congestion, as well as to balance the video qualities among the competing streams. In this paper, we present a unified optimization framework for video rate allocation over wireless networks. Our framework applies to both unicast and multicast sessions, and accommodates both scalable and non-scalable streams. The optimization objective is to minimize the total distortion of all video streams without incurring excessive network utilization. Our system model explicitly accounts for heterogeneity in wireless link capacities, traffic contention among neighboring links, as well as different video rate-distortion (RD) characteristics. The proposed distributed media-aware rate allocation scheme leverages cross-layer information exchange between the MAC and application layers to achieve fast convergence at the optimal allocation.We evaluate performance of the proposed scheme for streaming of high-definition (HD) and standard-definition (SD) video sequences over 802.11-based wireless networks, both in unicast and multicast scenarios. The scheme consistently outperforms conventional TCP-Friendly Rate Control (TFRC) in terms of overall video quality, and achieves more balanced qualities among the streams.     

Dynamic resource allocation algorithm in multi-user cooperative OFDMA systems: considering QoS and fairness constraints

Wireless transmission systems are constrained by several parameters such as the available spectrum bandwidth, mobile battery energy, transmission channel impairments and users’ minimum quality-of-service. In this paper, a new strategy is investigated that aims at improving the allocation of resources in a dual hop OFDMA cooperative network consisting in multi source–destination pairs and multiple decode-and-forward relays. First, the joint optimization of three types of resources: power, sub-channel and relay nodes, is formulated as a problem of subchannel-relay assignment and power allocation, with the objective of minimizing overall transmission power under the bit-error-rate and data rate constraints. However, the optimal solution to the optimization problem is computationally complex to obtain and may be unfair. Assuming knowledge of the instantaneous channel gains for all links in the entire network, an iterative three-step resource allocation algorithm with low complexity is proposed. In order to guarantee the fairness of users, several fairness criteria are also proposed to provide attractive trade-offs between network performance (i.e. overall transmission power, average network lifetime and average outage probability) and fairness to all users. Numerical studies are conducted to evaluate the performance of the proposed algorithm in two practical scenarios. Simulation results show that the proposed allocation algorithm achieves an efficient trade-off between network performance and fairness among users.     

Quality-driven cross-layer optimized video delivery over LTE

3GPP Long Term Evolution is one of the major steps in mobile communication to enhance the user experience for next-generation mobile broadband networks. In LTE, orthogonal frequency- division multiple access is adopted in the downlink of its E-UTRA air interface. Although cross-layer techniques have been widely adopted in literature for dynamic resource allocation to maximize data rate in OFDMA wireless networks, application-oriented quality of service for video delivery, such as delay constraint and video distortion, have been largely ignored. However, for wireless video delivery in LTE, especially delay-bounded real-time video streaming, higher data rate could lead to higher packet loss rate, thus degrading the user-perceived video quality. In this article we present a new QoS-aware LTE OFDMA scheduling algorithm for wireless real-time video delivery over the downlink of LTE cellular networks to achieve the best user-perceived video quality under the given application delay constraint. In the proposed approach, system throughput, application QoS constraints, and scheduling fairness are jointly integrated into a cross-layer design framework to dynamically perform radio resource allocation for multiple users, and to effectively choose the optimal system parameters such as modulation and coding scheme and video encoding parameters to adapt to the varying channel quality of each resource block. Experimental results have shown significant performance enhancement of the proposed system.     

Multiuser Distortion Management of Layered Video over Resource Limited Downlink Multicode-CDMA

Transmitting multiple real-time encoded videos to multiple users over wireless cellular networks is a key driving force for developing broadband technology. We propose a new framework to transmit multiple users' video programs encoded by MPEG-4 FGS codec over downlink multicode CDMA networks in real time. The proposed framework jointly manages the rate adaptation of source and channel coding, CDMA code allocation, and power control. Subject to the limited system resources, such as the number of pseudo-random codes and the maximal power for CDMA transmission, we develop an adaptive scheme of distortion management to ensure baseline video quality for each user and further reduce the overall distortion received by all users. To efficiently utilize system resources, the proposed scheme maintains a balanced ratio between the power and code usages. We also investigate three special scenarios where demand, power, or code is limited, respectively. Compared with existing methods in the literature, the proposed algorithm can reduce the overall system's distortion by 14% to 26%. In the demand-limited case and the code-limited but power-unlimited case, the proposed scheme achieves the optimal solutions. In the power-limited but code-unlimited case, the proposed scheme has a performance very close to a performance upper bound     

基于硬件损伤的异构网络鲁棒安全资源分配算法

针对多蜂窝多用户异构网络中收发机处信号畸变、用户信息泄露和传输中断等问题,该文提出一种基于硬件损伤的异构网络鲁棒安全资源分配算法。考虑小蜂窝用户最小安全速率约束、小蜂窝基站最大发射功率约束和宏用户干扰功率约束,建立了基于有界信道不确定性的能效最大化资源分配模型。基于Dinkelbach法、最坏准则法和连续凸近似理论,将原非凸资源分配问题等价转换为凸优化问题,并利用拉格朗日对偶算法得到解析解。仿真结果表明,与现有算法相比,所提算法具有较好的能效和鲁棒性。     

From rate-distortion analysis to resource-distortion analysis

The ultimate goal in communication system design is to control and optimize the system performance under resource constraints. As the communication paradigm evolves from the conventional desktop computing, wired, and centralized communication to current mobile, wireless, distributed, and massive communication, video encoding and transmission operate under more and more resource constraints. In traditional video communication applications, such as digital TV broadcast, the major constraint is in the form of transmission bandwidth or storage space, which determines the encoding bit rate. Rate-distortion (R-D) theories have been developed to model the relationship between the coding bit rate and signal distortion. For video communication over mobile devices, the video encoding and transmission operate under additional resource constraints, such as energy supply and on-board computation capability. Therefore, there is a need to extend the traditional R-D analysis to resource-distortion analysis by incorporating the new resource constraints into the R-D analysis framework. In distributed and massive wireless video sensor networks, the resource utilization behaviors of individual video sensors should be well-coordinated through network-level rate allocation and optimum routing so as to maximize the overall performance. In this paper, we start from the classical R-D theory developed by Shannon over 50 years ago, and then review the R-D modelling techniques for modern image and video compression systems. We study the resource-distortion analysis framework for video communication over wireless devices. As one step further, we present the research problem of resource allocation and performance optimization for video compression and communication over a network of wireless communication devices.     

Scalable Video Multicast Over Multi-Antenna OFDM Systems

We propose a framework for efficient scalable video multicast over downlink orthogonal frequency-division multiplexing (OFDM) systems with multiple transmit antennas. In conventional video multicast systems, the achievable transmission rate is determined by the user with the worst channel condition, and the system saturates the capacity when the number of users increases. To accommodate the heterogeneous channel conditions and device capabilities of various users, scalable video coding (SVC) encodes video streams into base and enhancement layers. We exploit the advances in multi-antenna OFDM and the layered nature of SVC, and propose a framework for scalable video multicast which guarantees the base layer quality for all users while making best use of limited resource for the enhancement layer of users with good channel conditions. We show that the resource allocation that includes the transmit precoding, subcarrier allocation, and bit and power allocation is a very difficult optimization problem. A low-complexity suboptimal algorithm is proposed which is suitable for practical implementations. Simulation results are provided to show the effectiveness of the proposed solution.     

Advances in Efficient Resource Allocation for Packet-Based Real-Time Video Transmission

Multimedia applications involving the transmission of video over communication networks are rapidly increasing in popularity. Such applications can greatly benefit from adapting video coding parameters to network conditions as well as adapting network parameters to better support the application requirements. These two dimensions can both be viewed as allocating source and network resources to improve video quality. We highlight recent advances in optimal resource allocation for real-time video communications over unreliable and resource constrained communication channels. More specifically, we focus on point-to-point coding and delivery schemes in which the sequences are encoded on the fly. We present a high-level framework for resource-distortion optimization. The framework can be used for jointly considering factors across network layers, including source coding, channel resource allocation, and error concealment. For example, resources can take the form of transmission energy in a wireless channel, and transmission cost in a DiffServ-based Internet channel. This framework can be used to optimally trade off resource consumption with end-to-end video quality in packet-based video transmission. After giving an overview of this framework, we review recent work in two areas-energy efficient wireless video transmission and resource allocation for Internet-based applications.     

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.     

超密集网络中最大化网络吞吐量的预测资源分配

在超密集网络中,小区间干扰严重制约了小区边缘用户的性能体验以及网络吞吐量。无线大数据分析的飞速发展,使得人们有可能通过预测未来的信道状态来分配资源,在无干扰网络中可达到很大的性能增益。但是在干扰网络中如何利用预测信息,在分配资源的同时有效协调干扰还是一个尚未研究的问题。本文分析了干扰网络中预测资源分配的设计难点和存在的问题,针对该问题提出了相应的解决方法,将资源分配建模成一个凸优化问题,通过求解优化问题得到最优的资源分配方法。仿真表明,与未知预测信息的最大化网络吞吐量方法相比,所提方法能够有效提高用户的成功传输率、平均传输进度和网络的吞吐量。当用户数据需求较大时,所提方法可以提供较大的网络性能增益。      

An overview of scheduling algorithms in MIMO-based fourth-generation wireless systems

In this article an overview of the scheduling algorithms proposed for fourth-generation multiuser wireless networks based on multiple-input multiple-output technology is presented. In MIMO systems a multi-user diversity gain can be extracted by tracking the channel fluctuations between each user and the base station, and scheduling transmission for the "best" user. Based on this idea, several opportunistic scheduling schemes that attempt to improve global capacity or satisfy users with different QoS requirements have been proposed. Transmit beamforming procedures aimed at increasing the channel fluctuations have been proposed. The simultaneous exploitation of both spatial and multi-user diversity is not straightforward; however, it may be achieved by a refined selection of the "best" user. In addition, a multiple access gain can be obtained from a simple SDMA/TOMA system. Finally, several resource allocation schemes are discussed for this hybrid multiple access system.     

无线协作网络中基于数据传输需求的分布式功率控制

在未来无线通信网络中,协作通信的性能依赖于通信资源的有效分配,比如中继选择和功率控制等.在本文中,我们建议了一个分布式买者和卖者博弈理论框架,以满足用户链路质量需求为基础,解决多用户协作通信中最优化中继选择和功率控制.本文联合考虑了源节点和中继节点的功率分配,进而优化源节点和中继节点的收益.这里提出的方法不仅有助于源节点找到相对位置较好的中继节点以及在源和中继之间进行最优化功率分配从而最小化源节点的支付,而且有助于相互竞争的中继节点提供优化的价格以最大化它们各自的收益.此外,这里的优化价格可以仅由局部信道状态信息和其他节点的能量价格决定.如果获得的中继节点总数增加,全网的能量消耗会更低.     

Cross-layer optimization of wireless networks using nonlinear column generation

We consider the problem of finding the jointly optimal end-to-end communication rates, routing, power allocation and transmission scheduling for wireless networks. In particular, we focus on finding the resource allocation that achieves fair end-to-end communication rates. Using realistic models of several rate and power adaption schemes, we show how this cross-layer optimization problem can be formulated as a nonlinear mathematical program. We develop a specialized solution method, based on a nonlinear column generation technique, and prove that it converges to the globally optimal solution. We present computational results from a large set of networks and discuss the insight that can be gained about the influence of power control, spatial reuse, routing strategies and variable transmission rates on network performance.     

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     

A Novel Immune Optimization Algorithm for Fairness Resource Allocation in Cognitive Wireless Network

Cognitive wireless network (CWN) is a novel concept for improving the utilization of scarce wireless spectrum resources. Dynamic resource allocation is an important task in such systems. In this paper, a novel resource allocation algorithm for multi-user OFDM-based CWN is presented. It is formulated into a constraint problem, and an optimization algorithm based on novel immune clonal is proposed. The proposed algorithm fully takes into account the maximum tolerable interferences of primary user and the proportional fairness for secondary user. The suitable operators for solving the problem are designed, such as clonal, mutation, Baldwin learning, selection and so on. The simulation results show that the proposed algorithm achieves high system throughput with proportional fairness among the secondary users.