OFDMA系统基于QoS保证和最大最小公平性准则下的动态资源分配

正交频分多址(OFDMA)技术以其更高的频谱效率和抗多径衰落特性成为高速无线通信网络的候选标准。兼顾效率和公平性是OFDMA系统资源分配亟待解决的问题。本文研究了OFDMA系统中的无线资源分配问题,既要保证QoS用户的最小速率要求,同时“尽力而为”用户之间必须满足最小速率最大化公平性(max-min fairness)准则;该资源分配问题可以表述为一个系统总功率约束下的子载波分配和功率控制的混合离散型优化模型,这是难解的NP-hard问题,穷举搜索的代价是极其巨大的。针对该非凸模型,本文设计一个拉格朗日松弛的优化算法,该算法中采用修正的椭球算法求解对偶问题。算法具有多项式时间复杂度,且与子载波数目呈线性增长关系。仿真结果表明,该算法能近似最优地满足用户QoS及最大最小公平性要求。      

Fair Radio Resource Allocation for MIMO OFDM-based Multicast Systems

This paper investigates the problem of resource allocation in a multiple-input multiple-output (MIMO) OFDM-based system, wherein multiple multicast groups exist. Multicasting is a transmission technique which enables a transmitter to communicate via a single wireless link with multiple receivers simultaneously. Moreover, the presence of multiple antennas in both transmitter and receiver enhances significantly the system spectral efficiency. MIMO technology along with multicasting offers major advantages to wireless systems. However, optimum exploitation of these technologies adds significant complexity to the system which makes very difficult any possible practical implementation. Another important issue of such systems is their capacity to ensure to all users a certain level of QoS. To that end, we propose a low complexity fair resource allocation algorithm aiming at ensuring a certain amount of resources to all users when multicasting is applied. Validation of the proposed solution is achieved through extensive simulation and it is compared to other multicast schemes for MIMO systems which exist in literature. Numerical results and complexity analysis show the feasibility of the proposed algorithm.     

Adaptive subcarrier and bit allocation in OFDMA systems supporting heterogeneous services

Orthogonal Frequency Division Multiple Access (OFDMA) is an efficient multiple access method for the future wireless systems. This paper studies the adaptive subcarrier and bit allocation problem in OFDMA systems to support heterogeneous services. The goal of the considered resource optimization technique is to maximize the total system throughput under the overall transmit power constraint while guaranteeing the QoS requirement of realtime users and supporting proportional fairness among non-realtime users. First, we introduce a Rate Adaptive (RA) resource allocation algorithm for non-realtime users and a Margin Adaptive (MA) algorithm for realtime users. Then, based on the previous algorithms, a novel algorithm is proposed to allocate the resource to both classes of users, which makes an efficient tradeoff between the resource usage of realtime users and non-realtime users. The algorithm is locally optimal solution provided that the MA and RA algorithms are utilized. Also, to reduce the computational complexity, a suboptimal method based on the balancing of the average power per subcarrier is also introduced. Monte Carlo simulation results show that all the proposed algorithms outperform the existing counterparts. The results also show that the suboptimal method for heterogeneous services can efficiently reduce the computational complexity at the cost of very little performance degradation. This work was supported by the National Natural Science Foundation of China (Nos. 60472079, 60572115), and by the Natural Science Foundation of Zhejiang Province (No. Z104252), China.     

下行多业务OFDMA系统中基于有效容量的资源分配算法研究

该文对多业务OFDMA系统的下行链路资源分配进行了研究,侧重考虑了实时业务用户的QoS要求,建立2维马尔可夫无线信道模型,采用自适应调制技术、有效容量理论以及有效带宽理论,为实时用户分配资源;并实现了非实时业务用户、尽力而为业务用户的资源分配。仿真结果表明,所提算法保证了下行OFDMA系统吞吐量的同时,在实时业务的延时和丢包率等方面都有一定的优越性。     

Wireless Packet Scheduling Algorithm for OFDMA System Based on Time‐Utility and Channel State

In this paper, we propose an urgency‐ and efficiencybased wireless packet scheduling (UEPS) algorithm that is able to schedule real‐time (RT) and non‐real‐time (NRT) traffics at the same time while supporting multiple users simultaneously at any given scheduling time instant. The UEPS algorithm is designed to support wireless downlink packet scheduling in an orthogonal frequency division multiple access (OFDMA) system, which is a strong candidate as a wireless access method for the next generation of wireless communications. The UEPS algorithm uses the time‐utility function as a scheduling urgency factor and the relative status of the current channel to the average channel status as an efficiency indicator of radio resource usage. The design goal of the UEPS algorithm is to maximize throughput of NRT traffics while satisfying quality‐of‐service (QoS) requirements of RT traffics. The simulation study shows that the UEPS algorithm is able to give better throughput performance than existing wireless packet scheduling algorithms such as proportional fair (PF) and modifiedlargest weighted delay first (M‐LWDF), while satisfying the QoS requirements of RT traffics such as average delay and packet loss rate under various traffic loads.     

Graph‐based resource allocation algorithms for multiuser downlink MIMO‐OFDMA networks

Multiuser multiple‐input multiple‐output orthogonal frequency division multiple access (MIMO‐OFDMA) is considered as the practical method to attain the capacity promised by multiple antennas in the downlink direction. However, the joint calculation of precoding/beamforming and resource allocation required by the optimal algorithms is computationally prohibitive. This paper proposes computationally efficient resource allocation algorithms that can be invoked after the precoding and beamforming operations. To support stringent and diverse quality of service requirements, previous works have shown that the resource allocation algorithm must be able to guarantee a specific data rate to each user. The constraint matrix defined by the resource allocation problem with these data rate constraints provides a special structure that lends to efficient solution of the problem. On the basis of the standard graph theory and the Lagrangian relaxation, we develop an optimal resource allocation algorithm that exploits this structure to reduce the required execution time. Moreover, a lower‐complexity suboptimal algorithm is introduced. Extensive simulations are conducted to evaluate the computational and system‐level performance. It is shown that the proposed resource allocation algorithms attain the optimal solution at a much lower computational overhead compared with general‐purpose optimization algorithms used by previous MIMO‐OFDMA resource allocation approaches. Copyright © 2012 John Wiley & Sons, Ltd.     

QoS aware adaptive resource allocation techniques for fair scheduling in OFDMA based broadband wireless access systems

A system based on orthogonal frequency division multiple access (OFDMA) has been developed to deliver mobile broadband data service at data rates comparable to those of wired services, such as DSL and cable modems. We consider the resource allocation problem of assigning a set of subcarriers and determining the number of bits to be transmitted for each subcarrier in OFDMA systems. We compare simplicity, fairness and efficiency of our algorithm with the optimal and proposed suboptimal algorithms for varying values of delay spread, number of users and total power constraint. The results show that the performance of our approach is appealing and can be close to optimal. We also consider another resource allocation scheme in which there is no fixed QoS requirements per symbol but capacity is maximized.     

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‐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.     

A resource‐tuned QoS multicast routing protocol

This paper presents a novel framework for quality‐of‐service (QoS) multicast routing with resource allocation that represents QoS parameters, jitter delay, and reliability, as functions of adjustable network resources, bandwidth, and buffer, rather than static metrics. The particular functional form of QoS parameters depends on rate‐based service disciplines used in the routers. This allows intelligent tuning of QoS parameters as functions of allocated resources during the multicast tree search process, rather than decoupling the tree search from resource allocation. The proposed framework minimizes the network resource utilization while keeping jitter delay, reliability, and bandwidth bounded. This definition makes the proposed QoS multicast routing with resource allocation problem more general than the classical minimum Steiner tree problem. As an application of our general framework, we formulate the QoS multicast routing with resource allocation problem for a network consisting of generalized processor sharing nodes as a mixed‐integer quadratic program and find the optimal multicast tree with allocated resources to satisfy the QoS constraints. We then present a polynomial‐time greedy heuristic for the QoS multicast routing with resource allocation problem and compare its performance with the optimal solution of the mixed‐integer quadratic program. The simulation results reveal that the proposed heuristic finds near‐optimal QoS multicast trees along with important insights into the interdependency of QoS parameters and resources.     

MIMO Based Radio Resource Management for UMTS Multicast Broadcast Multimedia Services

MIMO systems promise high performance gains over conventional single antenna systems. To accomplish high data rates over wireless links the use of multiple transmit and receive antennas is an alternative that does not require any extra bandwidth. It has the potential to address the unprecedented demand for wireless services, particularly for the Multimedia Broadcast Multicast Service (MBMS). This service supports downlink streaming and download-and-play type services to large groups of users. From the radio perspective, MBMS includes point-to-point (PtP) and point-to-multipoint (PtM) modes. New proposed MBMS related enhancements in the physical layer specifications and their effects on resource requirements are presented in this paper, such as the use of High Speed Downlink Packet Access (HSDPA) to broadcast/multicast video streaming using the Deficit Round Robin (DRR) scheduler algorithm as a way to maintain an acceptable QoS for all the users. Other improvements, based on the use of MIMO including macro-diversity, are independent of the mode used and are dependent on deployment scenarios, but can yield substantial reduction in resource demand.     

Joint scheduling and mapping in support of downlink fairness and spectral efficiency in ieee 802.16e OFDMA system

The next generation broadband wireless networks deploy orthogonal frequency division multiple access (OFDMA) as the enabling technologies for broadband data transmission with QoS capabilities. In such broadband wireless systems, one major issue is how to utilize radio resource efficiently while maintaining fairness between sessions as well as providing adequate QoS. In this work, we propose an approach for OFDMA/time division duplex (TDD) downlink suitable for IEEE802.16e WiMAX systems that combines scheduling and burst mapping algorithms for a trade‐off between session fairness, QoS, and spectral efficiency. While optimizing radio resources under QoS and fairness constraints is an NP‐hard problem, we follow a heuristic approach that simplifies the complexity of the algorithm. Performance results show that while the new scheme outperforms the Proportional Fair algorithm in terms of fairness, it also improves the overall system spectral efficiency. Copyright © 2016 John Wiley & Sons, Ltd.     

Cross‐layer 1 and 5 user grouping/power allocation/subcarrier allocations for downlink OFDMA/NOMA video communications

Wang et al proposed cross‐layer resource allocation for orthogonal frequency division multiple access (OFDMA) video transmission systems. Unlike Wang et al, we add non‐orthogonal multiple access (NOMA) to the downlink OFDMA video transmission system and propose power allocation for users on each subcarrier (cluster) to minimize sum of video mean square error (MSE) to increase the peak signal‐to‐noise ratio (PSNR), the video quality. For OFDMA/NOMA video communication systems, we propose cross‐layer user clustering to reassign the subcarriers based on sum video distortion minimization and derive the optimal power allocation among NOMA users on the same subcarrier to minimize the sum video distortion. Numerical results show that the proposed scheme outperforms the previous OFDMA cross‐layer scheme by Wang et al by 2.2 to 4.5 dB in PSNR and previous OFDMA NOMA physical layer scheme by Ali et al by 2 to 4.4 dB in PSNR, when SNR = 15 dB, and the number of users is 6 to 12.     

Cross‐Layer Resource Allocation Scheme for WLANs with Multipacket Reception

Tailored for wireless local area networks, the present paper proposes a cross‐layer resource allocation scheme for multiple‐input multiple‐output orthogonal frequency‐division multiplexing systems. Our cross‐layer resource allocation scheme consists of three stages. Firstly, the condition of sharing the subchannel by more than one user is studied. Secondly, the subchannel allocation policy which depends on the data packets’ lengths and the admissible combination of users per subchannel is proposed. Finally, the bits and corresponding power are allocated to users based on a greedy algorithm and the data packets’ lengths. The analysis and simulation results demonstrate that our proposed scheme not only achieves significant improvement in system throughput and average packet delay compared with conventional schemes but also has low computational complexity.     

Maximum Achievement Rate Allocation Algorithm for Downlink Multi-User OFDMA Systems

In multi-user OFDMA systems, adaptive resource allocation has been identified as one of the key technologies to have more flexibility and higher efficiency. Several adaptive subcarrier allocation algorithms with the objective to maximize spectral efficiency or fairness have been proposed. However, quality of service (QoS) requirement of each user may not be supported. Some algorithms considering user’s QoS requirement have been introduced, but they do not consider the case that every user’s QoS requirement cannot be guaranteed with limited resources. In this paper, we propose a maximum achievement rate allocation (MARA) algorithm as a new adaptive resource allocation algorithm. The proposed MARA algorithm has a goal to improve overall throughput while maximizing achievement rate, i.e., maximize the number of users meeting QoS requirements. In addition, we investigate that MARA is more effective when fractional frequency reuse (FFR) is adopted as a frequency partitioning scheme. Simulation results show that the MARA algorithm improves the achievement rate as well as overall throughput. Moreover, further performance gains are achieved when FFR is adopted.     

OFDMA系统中基于多目标优化的无线资源分配算法

本文提出了OFDMA系统中基于多目标优化的无线资源分配算法.针对不同业务的QoS要求,建立多目标优化模型,并提出一种多业务分级分配算法通过确定优先级、引入合适的参数获得次优解.仿真结果表明,该算法不但能够保证不同业务的QoS要求,而且能够兼顾相同业务的用户之间的公平性.     

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.     

A low-complexity beamforming-based scheduling to downlink OFDMA/SDMA systems with multimedia traffic

In this paper, we propose a low-complexity beamforming-based scheduling scheme utilizing a semi-orthogonal user selection (SUS) algorithm in downlink orthogonal frequency division multiple access (OFDMA)/space division multiple access (SDMA) systems to support multimedia traffic. One of the challenges in the multi-dimensional (space, time, and frequency) radio resource allocation problem for OFDMA/SDMA systems is its high complexity, especially to simultaneously satisfy the quality of services (QoS) requirements for various traffic classes. In the literature, the SUS algorithm is usually applied to the single-class traffic environment, but extending the SUS algorithm to the multimedia environment is not straightforward because of the need to prioritize the real-time (RT) users and the non-real-time (NRT) users. To solve this problem, we propose the concept of urgency value to guarantee the fairness of the NRT as well as the best effort (BE) users while satisfying the delay requirement for the RT users. Simulation results show that, when traffic load is greater than 0.5, the proposed scheduling algorithm can improve the fairness performance by more than 100% over the most recently proposed algorithms.     

Enabling seamless multimedia wireless access through QoS‐based bandwidth adaptation

Effective support of real‐time multimedia applications in wireless access networks, viz. cellular networks and wireless LANs, requires a dynamic bandwidth adaptation framework where the bandwidth of an ongoing call is continuously monitored and adjusted. Since bandwidth is a scarce resource in wireless networking, it needs to be carefully allocated amidst competing connections with different Quality of Service (QoS) requirements. In this paper, we propose a new framework called QoS‐adaptive multimedia wireless access (QoS‐AMWA) for supporting heterogeneous traffic with different QoS requirements in wireless cellular networks. The QoS‐AMWA framework combines the following components: (i) a threshold‐based bandwidth allocation policy that gives priority to handoff calls over new calls and prioritizes between different classes of handoff calls by assigning a threshold to each class, (ii) an efficient threshold‐type connection admission control algorithm, and (iii) a bandwidth adaptation algorithm that dynamically adjusts the bandwidth of an ongoing multimedia call to minimize the number of calls receiving lower bandwidth than the requested. The framework can be modeled as a multi‐dimensional Markov chain, and therefore, a product‐form solution is provided. The QoS metrics—new call blocking probability (NCBP), handoff call dropping probability (HCDB), and degradation probability (DP)—are derived. The analytical results are supported by simulation and show that this work improves the service quality by minimizing the handoff call dropping probability and maintaining the bandwidth utilization efficiently. Copyright © 2006 John Wiley & Sons, Ltd.     

Nash bargaining solution based joint time‐frequency‐code‐power resource management algorithm for TD‐LTE systems

This paper presents a joint time‐frequency‐code‐power resource management algorithm based on the Nash bargaining solution in time‐division long term evolution systems. First, a joint radio resource allocation scheme at the time, frequency, code and power domain simultaneously is provided for the time‐division long term evolution system. Second, the proposed algorithm is modeled as a cooperative game under the constraints of each user's minimal rate requirement and available resources, for example, the maximal transmitting power. To reduce the computational complexity, the joint resource allocation algorithm is divided into time‐frequency‐code and power domain resource allocation. Also, we could approach the Pareto optimal rate as closely as possible by iterations. Simulation results show that compared with the other resource allocation algorithms, the proposed algorithm has achieved a good tradeoff between the overall system throughput and fairness among different users. Copyright © 2012 John Wiley & Sons, Ltd.