Utility optimization scheduling for multi-point video surveillance in ubiquitous network

Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considering only wireless networks are not suitable for the ubiquitous network environment, and they will harm the interest of individual users with instable resource requirements. This paper considers the multi-point video surveillance scenarios in a complex network environment with both wired and wireless networks. We introduce the utility estimated by the total costs of an individual network user. The problem is studied through mathematical modeling and we propose an improved problem-specific branch-and-cut algorithm to solve it. The algorithm follows the divide-and-conquer principle and fully considers the duality feature of network selection. The experiment is conducted by simulation through C and Lingo. And it shows that compared with a centralized random allocation scheme and a cost greed allocation scheme, the proposed scheme has better per- formance of reducing the total costs by 13.0% and 30.6% respectively for the user.     

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     

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.     

Utility‐based resource allocation in uplink of OFDMA‐based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum opportunistically on the basis of non‐interfering to licensed users. This paper addresses the problem of resource allocation for multiaccess channel (MAC) of OFDMA‐based cognitive radio networks. The objective is to maximize the system utility, which is used as an approach to balance the efficiency and fairness of wireless resource allocation. First, a theoretical framework is provided, where necessary and sufficient conditions for utility‐based optimal subcarrier assignment and power allocation are presented under certain constraints. Second, based on the theoretical framework, effective algorithms are devised for more practical conditions, including ellipsoid method for Lagrangian multipliers iteration and Frank–Wolfe method for marginal utilities iteration. Third, it is shown that the proposed scheme does not have to track the instantaneous channel state via an outage‐probability‐based solution. In the end, numerical results have confirmed that the utility‐based resource allocation can achieve the optimal system performance and guarantee fairness. Copyright © 2009 John Wiley & Sons, Ltd.     

Resource planning and incentive engineering for a congested wireless access point: an integrated multiple time scale control mechanism

Wireless networks are playing an increasingly important role for global communications. Many resource allocation mechanisms have been proposed to efficiently utilize the limited radio resources in wireless networks to support a large number of mobile users with a diversity of applications. Among them, pricing frameworks that provide incentives to users to maximize their individual utility while optimizing allocation of network resources have attracted a lot of attention recently. Nevertheless, most of these pricing schemes require dynamic charging rates and may be too complex for wide acceptance by users, as most users would prefer relatively simple charging schemes. Moreover, use of a pricing framework to facilitate resource planning and future expansion at the service provider’s side has not yet been widely considered. In this paper, we propose Integrated Multiple Time Scale Control (IMTSC), a novel incentive engineering mechanism to facilitate resource allocation and network planning. Over different time scales, IMTSC combines the functions of network capacity planning, admission control for resource allocation, and tracking of users’ instantaneous traffic demands. The proposed mechanism is applied for access control at a congested access point in a wireless network. By decomposing the original problem into distributed optimization problems that are solved locally by the service provider through adjusting charging rate and remotely by individual users by appropriately changing her service requests, we show that maximization of user’s utility and increase of network efficiency can be simultaneously achieved. Results from extensive simulations demonstrate the effectiveness of the proposed IMTSC mechanism.     

A Bidding Algorithm for Optimized Utility-Based Resource Allocation in Ad Hoc Networks

This article proposes a scheme for bandwidth allocation in wireless ad hoc networks. The quality of service (QoS) levels for each end-to-end flow are expressed using resource-utility functions, and our algorithms aim to maximize aggregated utility. The shared channel is modeled as bandwidth resources defined by maximal cliques of mutual interfering links. We propose an entirely novel resource allocation algorithm that employs auction mechanisms where flows are bidding for resources. The bids depend both on the flow's utility function and the intrinsically derived shadow prices. Then we combine it with a utility-aware on-demand shortest path routing algorithm where shadow prices are used as a natural distance metric. We also show that the problem can be formulated as a linear programming problem. Thus we can compare the performance of our scheme to the centralized optimal LP solution, registering results very close to the optimum. We isolate the performance of the price-based routing and show its advantages in hotspot scenarios, and also propose an asynchronous version that is more feasible for ad hoc environments. Experimental results of a comparison with the state-of-the-art approach based on Kelly's utility maximization framework show that our approach exhibits superior performance for networks with both increased mobility or increased allocation period.     

Resource Allocation for Uncoded Multi-user Video Transmission over Wireless Networks

In wireless networks, multi-user video streaming under limited resource is a challenging problem. The main challenge is how to meet the transmission requirements under the different channel condition and video content complexity. In this paper, we propose an uncoded video transmission framework to deliver the multi-user video over wireless networks. In order to evaluate the overall performance of multi-user network more practically, three optimization strategies are proposed in this paper: 1) minimizing the total distortion; 2) minimizing the maximal distortion; 3) minimizing the summation of square root distortion. Furthermore, the corresponding joint resource allocation algorithms are developed to solve the optimization problems. The simulation results demonstrate that different optimization strategies have different resource allocation and performance for each user. The optimization strategy 1) performs the best in terms of average PSNR of all users, the optimization strategy 2) achieves more fair result, and the optimization strategy 3) achieves a good balance. The strategy 3) can improve the performance for users with bad channel condition, while little loss is caused for users with good channel condition.     

Resource scheduling scheme for 5G mmWave CP-OFDM based wireless networks with delay and power allocation optimizations

In this paper, to optimize the average delay and power allocation (PA) for system users, we propose a resource scheduling scheme for wireless networks based on Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM) according to the first fifth-generation standards. For delay minimization, we solve a throughput maximization problem that considers CP-OFDM systems with carrier aggregation (CA). Regarding PA, we consider an approach that involves maximizing goodput using an effective signal-to-noise ratio. An algorithm for jointly solving delay minimization through computation of required user rates and optimizing the power allocated to users is proposed to compose the resource allocation approach. In wireless network simulations, we consider a scenario with the following capabilities: CA, 256-Quadrature Amplitude Modulation, millimeter waves above 6 GHz, and a radio frame structure with 120 KHz spacing between the subcarriers. The performance of the proposed resource allocation algorithm is evaluated and compared with those of other algorithms from the literature using computational simulations in terms of various Quality of Service parameters, such as the throughput, delay, fairness index, and loss rate.     

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.     

Proportional Fairness in Multi-Channel Multi-Rate Wireless Networks-Part I: The Case of Deterministic Channels with Application to AP Association Problem in Large-Scale WLAN

This is Part I of a two-part paper series that studies the use of the proportional fairness (PF) utility function as the basis for resource allocation and scheduling in multichannel multi-rate wireless networks. The contributions of Part I are threefold. (i) We present the fundamental properties and physical/economic interpretation of PF optimality. We show that PF leads to equal airtime allocation to users for the singlechannel case; and equal equivalent airtime allocation to users for the multi-channel case. In addition, we also establish the Pareto efficiency of joint-channel PF optimal solution (the formulation of interest to us in this paper), and its superiority over the individual-channel PF optimal solution in that the individual user throughputs of the former are all equal to or greater than the corresponding user throughputs of the latter. (ii) Second, we derive characteristics of joint-channel PF optimal solutions useful for the construction of PF-optimization algorithms. In particular, we show that a PF solution typically consists of many zero airtime assignments when the difference between the number of users U and the number of channels S, |U ? S|, is large. We present several PF-optimization algorithms, including a fast algorithm that is amenable to parallel implementation. (iii) Third, we study the use of PF utility for resource allocation in large-scale WiFi networks consisting of many adjacent wireless LANs. We find that the PF solution simultaneously achieves higher system throughput, better fairness, and lower outage probability with respect to the default solution given by today?s 802.11 commercial products. Part II of this paper series extends our investigation to the time-varying-channel case in which the data rates enjoyed by users over the channels vary dynamically over time.     

一种新的认知无线电功率分配算法（英文）

Most resource allocation algorithms are based on interference power constraint in cognitive radio networks.Instead of using conventional primary user interference constraint,we give a new criterion called allowable signal to interference plus noise ratio(SINR) loss constraint in cognitive transmission to protect primary users.Considering power allocation problem for cognitive users over flat fading channels,in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user,we propose a new power allocation algorithm.The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.     

User scheduling and power allocation for nonfull buffer traffic in NOMA downlink systems

Nonorthogonal multiple access (NOMA) is one of the key technologies for 5G, where the system capacity can be increased by allowing simultaneous transmission of multiple users at the same radio resource. The most of the proportional fairness (PF)–based resource allocation studies for NOMA systems assumes full buffer traffic model, while the traffic in real‐life scenarios is generally nonfull buffer. In this paper, we propose User Demand–Based Proportional Fairness (UDB‐PF) and Proportional User Satisfaction Fairness (PUSF) algorithms for user scheduling and power allocation in NOMA downlink systems when traffic demands of the users are limited and time‐varying. UDB‐PF extends the PF‐based scheduling by allocating optimum power levels towards satisfying the traffic demand constraints of user pair in each resource block. The objective of PUSF is to maximize the network‐wide user satisfaction by allocating sufficient frequency and power resources according to traffic demands of the users. In both cases, user groups are selected first to simultaneously transmit their signals at the same frequency resource, while the optimal transmission power level is assigned to each user to optimize the underlying objective function. In addition, the genetic algorithm (GA) approach is employed for user group selection to reduce the computational complexity. When the user traffic rate requirements change rapidly over time, UDB‐PF yields better sum rate (throughput) while PUSF provides better network‐wide user satisfaction results compared with the PF‐based user scheduling. We also observed that the GA‐based user group selection significantly reduced the computational load while achieving the comparable results of the exhaustive search.     

分层异构网络中基于斯坦克尔伯格博弈的资源分配算法

分层异构网络中家庭基站与宏基站之间往往存在干扰,如何分配资源以获得高谱率和高容量、保证用户性能一直是研究的重点。为了解决这个问题,本文提出了一种异构蜂窝网络中基于斯坦克尔伯格博弈的家庭基站与宏基站联合资源分配算法,算法首先基于图论的分簇算法对家庭基站和宏用户进行分簇和信道分配,以减少家庭基站之间的同层干扰和家庭基站层与宏蜂窝网络的跨层干扰;然后建立了联合家庭基站发射功率以及宏用户接入选择的斯坦克尔伯格博弈,推导出达到纳什均衡时的家庭基站发射功率的表达式,并据此为宏用户选择合适的接入策略。仿真结果表明,该算法能够有效地提高宏用户的信干噪比（SINR）,家庭用户的性能也得到改善。      

Power control and channel allocation for real‐time applications in cellular networks

The next‐generation packet‐based wireless cellular network will provide real‐time services for delay‐sensitive applications. To make the next‐generation cellular network successful, it is critical that the network utilizes the resource efficiently while satisfying quality of service (QoS) requirements of real‐time users. In this paper, we consider the problem of power control and dynamic channel allocation for the downlink of a multi‐channel, multi‐user wireless cellular network. We assume that the transmitter (the base‐station) has the perfect knowledge of the channel gain. At each transmission slot, a scheduler allots the transmission power and channel access for all the users based on the instantaneous channel gains and QoS requirements of users. We propose three schemes for power control and dynamic channel allocation, which utilize multi‐user diversity and frequency diversity. Our results show that compared to the benchmark scheme, which does not utilize multi‐user diversity and power control, our proposed schemes substantially reduce the resource usage while explicitly guaranteeing the users' QoS requirements. Copyright © 2007 John Wiley & Sons, Ltd.     

OFDM-UWB系统基于用户速率的多用户动态资源分配算法

在原有动态资源分配算法基础上,提出了一种基于用户速率需求的动态资源分配算法。该算法在满足用户数据速率需求和服务质量要求(QoS)的前提下,以用户公平性为原则,分步执行子载波和比特分配来降低系统总的发射功率。首先,通过比较不同子载波对用户速率的影响,引入速率影响因子,对子载波进行分配;然后为每个用户子载波分配比特,并根据用户速率需求进行比特调整。为了进一步降低系统的复杂度,提出了一种通过子载波分组来完成子载波比特分配的方法。仿真结果表明,该算法能够降低系统功耗、误码率和系统复杂度。     

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.     

An econometric model for resource management in competitive wireless data networks

This article investigates the role and importance of the economic aspects that are vital to the success of wireless services deployment and provider selection by users in a competitive environment. We show how some of the econometric measures can meaningfully capture the user decisions/actions (e.g., churning) that can potentially be utilized by the providers in managing radio resources (e.g., bandwidth) in wireless data networks. In particular, by modeling the interaction between a service provider and its customers (or users) as a non-cooperative game, we propose a novel cross-layer resource management framework for integrated admission and rate control in CDMA networks. Analytical and simulation results demonstrate how the proposed framework can help minimize customer churning and maximize revenue for the wireless operators, yet optimizing customer satisfaction by providing differentiated quality of service to different classes of users.     

Dynamic Resource Allocation in CDMA Systems with Deterministic Codes and Multirate Provisioning

Next generation wireless CDMA systems will provide high and variable data rates by using multicode structures, controllable code spreading gains, and transmit power adaptation. We address the emerging resource allocation problem in that context and consider maximizing the total achievable user rate while satisfying minimum rate requirements of users. We devise symbol-synchronous and asynchronous models that capture different communication scenarios. The synchronous model holds for down-link transmission in one cell. The asynchronous model captures up-link single-cell communication and down-link or up-link scenarios in multicell systems. It can also account for multipath with each path corresponding to a virtual user. We propose a class of two-stage resource allocation algorithms. First, an admissible set of codes is constructed with criteria that capture code cross-correlation, induced interference to the system, and code rates. Next, the codes are allocated to users so as to satisfy their rate requirements. In the synchronous case, the problem structure allows the distinction of the two stages. In the asynchronous case, this distinction is not feasible due to different user delay profiles perceived at the receiver. Our models and numerical results indicate interesting trends and lead to useful conclusions and design guidelines for resource allocation algorithms under the aforementioned regimes     

A novel noncooperative game competing model using generalized simple additive weighting method to perform network selection in heterogeneous wireless networks

Network selection mechanisms have a significant role in guaranteeing the QoS for users in a heterogeneous wireless networks environment. These mechanisms allow the selection of an optimal wireless network to satisfy the needs of users. Users are provided with the opportunity to select from multiple connectivity opportunities available all over various wireless networks. Furthermore, the network operators themselves can execute active selection strategies that facilitate proper decision making, in which user preferences are considered. This study proposes a new noncooperative competing game‐theoretic model and strategy space based on user preference. This model can solve network selection problems and capture the inter‐linkages of decisions taken by various networks. A generalized simple additive weighting method is incorporated into the framework of noncooperative game theory. In addition, the utility function is employed to assess the usefulness of the system. Simulation results and analysis illustrate the efficacy of the suggested model in attaining optimum network utility for heterogeneous wireless networks while optimizing user satisfaction. Copyright © 2014 John Wiley & Sons, Ltd.     

An efficient data rate maximization algorithm for OFDM based wireless networks

In this paper we present a computationally efficient, suboptimal integer bit allocation algorithm that maximizes the overall data rate in multiuser orthogonal frequency division multiplexing (OFDM) systems implemented in wireless networks. Assuming the complete knowledge of a channel and allowing a subchannel to be simultaneously shared by multiple users we have solved this data rate maximization problem in two steps. The first step provides subchannel assignment to users considering the users’ requests on quality of service (QoS) expressed as the minimum signal-to-noise ratio (SNR) on each subchannel. The second step provides transmit power and bit allocation to subchannels in order to maximize the overall data rate. To reduce computational complexity of the problem we propose a simple method which assigns subchannels to users and distributes power and bits among them. We have analyzed the performance of our proposed algorithm by simulation in a multiuser frequency selective fading environment for various signal-to-noise ratios and various numbers of users in the system. We have concluded that our algorithm, unlike other similar algorithms, is suitable for OFDM wireless networks, especially when signal-to-noise ratio in the channel is low. Also, the results have shown that the total data rate grows with the number of users in the system.