A multi-cell graph based dynamic resource allocation scheme for multi-user wireless networks

Dynamic resource allocation being a computationally difficult problem, static spectrum management is more commonly used in large-scale networks. The combination of virtualization technologies, where powerful centralized allocation algorithms can be implemented, and recent advances in graph coloring algorithms prompts the revisiting of this view. We describe a new graph based framework to maximize the number of simultaneously communicating mobiles in a wireless network. Since the considered problem is NP-hard, we propose various heuristic algorithms and analyze their performance, in comparison with standard decentralized channel assignment strategies such as Fractional Frequency Reuse (FFR). We consider the LTE uplink and downlink with the WINNER channel as the reference model. We show that for blocking probabilities below 2%, our scheme typically increases the number of mobile users by 25%. For example with 25 base stations and 120 channels, running the resource allocation scheme takes one second on a PC and permits to increase the number of mobiles requiring one single channel each from 750 to 950, a 25% increase in efficiency compared to FFR.     

An uplink resource allocation scheme for OFDMA‐based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum unoccupied by licensed users. In cognitive radio networks, extra constraints on interference temperature need to be introduced into radio resource allocation. In this paper, the uplink radio resource allocation is investigated for OFDMA‐based cognitive radio networks. In consideration of the characteristics of cognitive radio and OFDMA, an improved water‐filling power allocation scheme is proposed under the interference temperature constraints for optimal performance. Based on the improved water‐filling power allocation, a simple subcarrier allocation algorithm for uplink is proposed. The subcarrier allocation rules are obtained by theoretical deduction. In the uplink subcarrier allocation algorithm, the subcarriers are allocated to the users with the best channel quality initially and then adjusted to improve the system performance. A cursory water‐filling level estimation method is used to decrease the complexity of the algorithm. Asymptotic performance analysis gives a lower bound of the stability of the water‐filling level estimation. The complexity and performance of the proposed radio resource allocation scheme are investigated by theoretical analysis and numerical results. Copyright © 2008 John Wiley & Sons, Ltd.     

Utility‐optimal cross‐layer resource allocation in distributed wireless cooperative networks

In this paper, we propose a distributed cross‐layer resource allocation algorithm for wireless cooperative networks based on a network utility maximization framework. The algorithm provides solutions to relay selections, flow pass probabilities, transmit rate, and power levels jointly with optimal congestion control and power control through balancing link and physical layers such that the network‐wide utility is optimized. Via dual decomposition and subgradient method, we solve the utility‐optimal resource allocation problem by subproblems in different layers of the protocol stack. Furthermore, by introducing a concept of pseudochannel gain, we model both the primal direct logical link and its corresponding cooperative transmission link as a single virtual direct logical link to simplify our network utility framework. Eventually, the algorithm determines its primal resource allocation levels by employing reverse‐engineering of the pseudochannel gain model. Numerical experiments show that the convergence of the proposed algorithm can be obtained and the performance of the optimized network can be improved significantly. Copyright © 2012 John Wiley & Sons, Ltd.     

Deep reinforcement learning based resource allocation algorithm in cellular networks

In order to solve multi-objective optimization problem,a resource allocation algorithm based on deep reinforcement learning in cellular networks was proposed.Firstly,deep neural network (DNN) was built to optimize the transmission rate of cellular system and to complete the forward transmission process of the algorithm.Then,the Q-learning mechanism was utilized to construct the error function,which used energy efficiency as the rewards.The gradient descent method was used to train the weights of DNN,and the reverse training process of the algorithm was completed.The simulation results show that the proposed algorithm can determine optimization extent of optimal resource allocation scheme with rapid convergence ability,it is obviously superior to the other algorithms in terms of transmission rate and system energy consumption optimization.     

QoS provisioning for multiple non‐real‐time services in cellular wireless networks

Future mobile services are expected to include various non‐voice oriented services. One important category of non‐voice oriented mobile services is non‐real‐time services. When a mobile user establishes a connection to access non‐real‐time service, the mobile user usually cares about whether the total time to complete its data transfer is within its time tolerance. In addition, different mobile users may have different bandwidth requirements and different tolerances in the total completion time. It is essential for wireless systems to provide various mobile users with different total completion times. In this paper, two quality‐of‐service (QoS) metrics, called stretch ratio and eligibility percentage, are employed at a connection level to present the degree of the length of the total completion time. We devise a measurement based call admission control scheme that provides multiple QoSs for various mobile users which have different requirements of stretch ratios, eligibility percentages, and bandwidths. Extensive simulation results show that the measurement based call admission control scheme not only provides various satisfactory QoSs for mobile users but also produces high throughput. Copyright © 2010 John Wiley & Sons, Ltd.     

Cross-layer radio resource allocation in packet CDMA wireless mobile networks

An efficient radio resource allocation scheme is crucial for guaranteeing the quality of service (QoS) requirements and fully utilizing the scarce radio resources in wireless mobile networks. Most of previous studies of radio resource allocation in traditional wireless networks concentrates on network layer connection blocking probability QoS. In this paper, we show that physical layer techniques and QoS have significant impacts on network layer QoS. We use a concept of cross-layer effective bandwidth to measure the unified radio resource usage taking into account both physical layer linear minimum-mean square error (LMMSE) receivers and varying statistical characteristics of the packet traffic in code devision multiple access (CDMA) networks. We demonstrate the similarity between traditional circuit-switched networks and packet CDMA networks, which enables rich theories developed in traditional wireless mobile networks to be used in packet CDMA networks. Moreover, since both physical layer signal-to-interference ratio (SIR) QoS and network layer connection blocking probability QoS are considered simultaneously, we can explore the tradeoff between physical layer QoS and network layer QoS in packet CDMA networks. This work is supported by Natural Science and Engineering Research Council of Canada. Please address all correspondence to Professor Vikram Krishnamurthy at the above address. Fei Yu received the Ph.D. degree in electrical engineering from the University of British Columbia in 2003. From 2002 to 2004, he was with Ericsson (in Lund, Sweden), where he worked on the research and development of dual mode UMTS/GPRS handsets. From 2005, he has been working in Silicon Valley at a start-up, where he conducts research and development in the areas of advanced wireless communication technologies and new standards. After completing the PhD, he has been a research associate in the Department of Electrical and Computer Engineering at the University of British Columbia. His research interests include cross-layer optimization, QoS provisioning and security in wireless networks. Vikram Krishnamurthy (S’90-M’91-SM’99-F’05) was born in 1966. He received his bachelor’s degree from the University of Auckland, New Zealand in 1988, and Ph.D. from the Australian National University, Canberra, in 1992. Since 2002, he has been a professor and Canada Research Chair at the Department of Electrical Engineering, University of British Columbia, Vancouver, Canada. Prior to this he was a chaired professor at the Department of Electrical and Electronic Engineering, University of Melbourne, Australia. His research interests span several areas including ion channels and nanobiology, stochastic scheduling and control, statistical signal processing and wireless telecommunications. Dr. Krishnamurthy has served as associate editor for IEEE Transactions on Signal Processing, IEEE Transactions Aerospace and Electronic Systems, IEEE Transactions Nanobioscience, IEEE Transactions Circuits and Systems II, Systems and Control Letters and European Journal of Applied Signal Processing. He was guest editor of a special issue of IEEE Transactions on NanoBioScience, March 2005 on bio-nanotubes.     

End-to-end utility-based resource allocation for multi-RAT nodes in heterogeneous cognitive wireless networks

This paper studies the problem of effective resource allocation for multi-radio access technologies (Multi-RAT) nodes in heterogeneous cognitive wireless networks (HCWNs). End-to-end utility, which is defined as the delay of end-to-end communication, is taken into account in this paper. In the scenario of HCWNs, it is assumed that the cognitive radio nodes have the ability of Multi-RAT and can communicate with each other through different paths simultaneously by splitting the arrival packets. In this paper, the problem is formulated as the optimization of split ratio and power allocation of the source cognitive radio node to minimize the delay of end-to-end communication, and a low complexity step-by-step iterative algorithm is proposed. Numerical results show good performance of the proposed algorithm over two other conventional algorithms.     

A self‐organized resource allocation scheme for heterogeneous macro‐femto networks

This paper investigates the radio resource management (RRM) issues in a heterogeneous macro‐femto network. The objective of femto deployment is to improve coverage, capacity, and experienced quality of service of indoor users. The location and density of user‐deployed femtos is not known a‐priori. This makes interference management crucial. In particular, with co‐channel allocation (to improve resource utilization efficiency), RRM becomes involved because of both cross‐layer and co‐layer interference. In this paper, we review the resource allocation strategies available in the literature for heterogeneous macro‐femto network. Then, we propose a self‐organized resource allocation (SO‐RA) scheme for an orthogonal frequency division multiple access based macro‐femto network to mitigate co‐layer interference in the downlink transmission. We compare its performance with the existing schemes like Reuse‐1, adaptive frequency reuse (AFR), and AFR with power control (one of our proposed modification to AFR approach) in terms of 10 percentile user throughput and fairness to femto users. The performance of AFR with power control scheme matches closely with Reuse‐1, while the SO‐RA scheme achieves improved throughput and fairness performance. SO‐RA scheme ensures minimum throughput guarantee to all femto users and exhibits better performance than the existing state‐of‐the‐art resource allocation schemes.Copyright © 2014 John Wiley & Sons, Ltd.     

A dynamic transmission capacity allocation scheme for wired/wireless ATM networks

The previous research on administration of the transmission capacity in the wired/ wireless ATM networks only focuses on wired part or wireless part. There are very few people do the work extending to the links associating with handoff in the whole network. This paper develops the algorithms of transmission capacity administration on the link connecting the base station and base station controller (including the air interface of the base station) and the VPs among the base station controllers in the wired/ wireless ATM networks, which adapt to the traffic state of each service in every cellular cell to allocate (provision) transmission capacity and to reserve handoff guard capacity on these links, respectively. By simulating and analyzing the performance of the algorithm, it is found that it does well for the multimedia communication in which the transmission capacity requirement of each service may be widely different, so that the network bandwidth resource can be used efficiently.     

光因特网中动态综合考虑的资源分配算法

该文研究了光因特网络中的动态资源分配问题，提出了基于分层图模型的路由选择和波长分配算法。对于动态变化的业务到达请求，如果在已有的基于IP级的逻辑拓扑上不能有效建立，则需要为该请求按算法分配资源，即解决路由选择和波长分配问题。由于该文算法将IP层和光层综合进行考虑，所以能大大提高资源利用的有效性，取得较好的阻塞性能。仿真结果表明，该算法既能选择比较短的路由，又能使网络取得较低的阻塞率。     

Joint route selection and resource allocation in multihop wireless networks based on a game theoretic approach

In this work we aim to design simple, distributed self-configuring solutions for the problem of route selection and channel and power allocation in multihop autonomous wireless systems using a game theoretic perspective. We propose and compare three games with different levels of complexity: a potential flow game where players need complete network knowledge, a local flow game requiring full information of the flow and a low complexity cooperative link game which works with partial information of the flow. All these games have been designed to always assure the convergence to a stable point in order to be implemented as distributed algorithms. To evaluate their quality, we also obtain the best achievable performance in the system using mathematical optimization. The system is modeled with the physical interference model and two different definitions of the network utility are considered: the number of active flows and the aggregated capacity in bps. Results show that the proposed games approach the centralized solution, and specially, that the simpler cooperative link game provides a performance close to that of the flow games.     

Optimal resource allocation scheme for cognitive radio networks with relay selection based on game theory

In this paper,we present a non-transferable utility coalition graph game(NTU-CGG) based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing(OFDMA) based cognitive radio networks to maximize both system throughput and system fairness.In this algorithm,with the assistance of others SUs,SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs.So this scheme can effectively exploit both space and frequency diversity of the system.Performance results show that,NTU-CGG significantly improves system fairness level while not reducing the throughput comparing with other existing algorithms.     

Radio resource allocation for interference management in mobile broadband OFDMA based networks

This paper focuses on the inter‐cell interference (ICI) management problem in the downlink channel for mobile broadband wireless OFDMA‐based systems. This subject is addressed from the standpoint of different interrelated resource allocation mechanisms operating in multi‐cell scenarios in order to exploit frequency and multi‐user diversity: ICI coordination/avoidance and adaptive subcarrier and power allocation. Even though these methods can be applied in a stand‐alone way, a significant performance improvement is achieved if they are jointly designed and operate in a combined basis. Several alternatives for mixed frequency and power ICI coordination schemes are proposed in this paper. Connected with a proper power mask‐based design, the potential gain of a flexible frequency sectorization solution, halfway between fractional/soft frequency reuse and pure frequency sectorization, is explored. The main objective is to outperform fractional/soft frequency reuse offering an attractive trade‐off between cell‐edge user data rates and average cell throughput. Proposals concerning ICI coordination/avoidance have been evaluated in combination with several heuristic adaptive subcarrier and power allocation algorithms. Copyright © 2009 John Wiley & Sons, Ltd.     

基于柔性QoS的资源动态分配策略研究

本文在对QoS的柔性,描述和评价方法进行研究的基础上,针对频率资源有限的无线ATM网,提出了利用QoS的柔性在业务过程中对频率资源进行动态分配的方案和算法,并进行了实验仿真,结果表明利用QoS的柔性动态分配频率资源可以提高资源的利用率。     

基于改进遗传算法的C-RAN网络动态无线资源分配

针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(Remote Radio Head,RRH)选择、子载波分配和RRH功率分配三个维度进行研究.首先,根据传统的C-RAN系统传输模型和QoS约束在时变业务环境下建立了以发射功率为变量,以吞吐量最大为优化目标的优化问题;然后,基于改进的遗传算法,将原优化方案转变为通过优化RRH选择、子载波分配和RRH功率分配来达到提高系统吞吐量的目的;最后,将改进的遗传算法与其他智能算法在种群规模变化下进行了时间复杂度对比.实验结果表明,所提算法具有较低时间复杂度,所提资源分配方案下的平均吞吐量增益为17％.     

A preemption‐based scheduling algorithm for WiMAX networks

Several scheduling techniques were designed for the base station (BS) of IEEE 802.16e wireless interoperability of microwave access networks. However, depending on the BS scheduler alone to determine the servicing order of each connection might affect the accuracy of the scheduling process because the BS does not necessarily have enough up‐to‐date information about the current state of the connections at the subscriber station. In this paper, we propose a preemption‐based scheduling algorithm that focuses on improving the quality of service requirements of real‐time service flow classes. The proposed algorithm incorporates two schedulers, one at the BS and another one at the subscriber station. We have implemented and integrated the proposed algorithm with the network simulator NS2 using the Network and Distributed Systems Laboratory wireless interoperability of microwave access module. Simulation results have shown that the proposed approach outperforms other scheduling algorithms in terms of enhancing the throughput and the average delay of real‐time quality of service classes. Copyright © 2013 John Wiley & Sons, Ltd.     

Opportunistic delay‐margin‐based resource allocation for next‐generation wireless networks

This paper studies and develops efficient traffic management techniques for downlink transmission at the base station (BS) of multi‐service IP‐based networks by combining quality‐of‐service (QoS) provision and opportunistic wireless resource allocation. A delay‐margin‐based scheduling (DMS) for downlink traffic flows based on the delays that each packet has experienced up to the BS is proposed. The instantaneous delay margin, represented by the difference between the required and instantaneous delays, quantifies how urgent the packet is, and thus it can determine the queuing priority that should be given to the packet. The proposed DMS is further integrated with the opportunistic scheduling (OPS) to develop various queueing architectures to increase the wireless channel bandwidth efficiency. Different proposed integration approaches are investigated and compared in terms of delay outage probability and wireless channel bandwidth efficiency by simulation. Copyright © 2010 John Wiley & Sons, Ltd.     

Adaptive radio resource allocation for multiple traffic OFDMA broadband wireless access system

1 Introduction Next-generation wireless communication systems (systems beyond 3G) will be required to provide flexible and easy deployment solution to high-speed communications and to support a variety of services utilizing advanced multiple access techni…     

Clustering‐based low‐complexity resource allocation in two‐tier femtocell networks with QoS provisioning

In this paper, we study the resource allocation problem of the uplink transmission with delay quality‐of‐service constraints in two‐tier femtocell networks. Particularly, to provide statistical delay guarantees, the effective capacity is employed as the network performance measure instead of the conventional Shannon capacity. To make the problem computationally efficient and numerically tractable, we decompose the problem into three subproblems, namely, cluster configuration subproblem, intra‐cluster subchannel allocation subproblem and inter‐cluster power control subproblem. Firstly, we develop a low‐complexity heuristic semi‐dynamic clustering scheme, where the delay of the channel state information feedback via backhaul is considered. We model such system in the framework of networked partial observation Markov decision process and derive a strategy to reduce the search range for the best cluster configuration. Then, for a given cluster configuration, the cluster heads deal with subchannel allocation and power control within each cluster. We propose a subchannel allocation scheme with proportional fairness. Thereafter, the inter‐cluster power control subproblem is modeled as a set of exact potential games, and a channel quality related pricing mechanism is presented to mitigate inter‐cluster interference. The existence and uniqueness of Nash equilibriums for the proposed game are investigated, and an effective decentralized algorithm with guaranteed convergence is designed. Simulation results demonstrate that the proposed algorithms not only have much lower computational complexity but also perform close to the exhaustive search solutions and other existing schemes. Copyright © 2015 John Wiley & Sons, Ltd.     

VoIP traffic in wireless mesh networks: a MOS‐based routing scheme

Support of Voice over Internet Protocol (VoIP) services in wireless mesh networks requires implementation of efficient policies to support low‐delay data delivery. Multipath routing is typically supported in wireless mesh networks at the network level to provide high fault tolerance and load balancing because links in the proximity of the wireless mesh gateways can be very stressed and overloaded, thus causing scarce performance. As a consequence of using multipath solutions, lower delay and higher throughput can be supported also when a given path is broken because of mobility or bad channel conditions, and alternative routes are available. This can be a relevant improvement especially when assuming that real‐time traffic, such as VoIP, travels into the network. In this paper, we address the problem of Quality of Service (QoS) support in wireless mesh networks and propose a multipath routing strategy that exploits the Mean Opinion Score (MOS) metric to select the most suitable paths for supporting VoIP applications and performing adaptive load balancing among the available paths to equalize network traffic. Performance results assess the effectiveness of the proposed approach when compared with other existing methodologies. Copyright © 2015 John Wiley & Sons, Ltd.