正交频分多址系统中一种面向多业务应用的自适应资源分配算法

针对正交频分多址(OFDMA)系统下行链路多业务自适应调度的问题,该文首先以最大化系统吞吐量为优化目标、每种业务的服务质量(QoS)保证为约束条件,建立了一种通用的多业务自适应资源分配模型。为解决此优化问题,提出了一种具体的自适应资源调度算法。该算法对实时业务按照用户选择最好的信道的原则分配尽可能少的资源以保证其QoS,对非实时业务把尽可能多的剩余资源按照信道选择最好的用户的原则进行分配,充分利用信道资源,提升系统容量。仿真结果表明,该算法保证了下行OFDMA系统吞吐量的同时,在实时业务的延时和丢包率等方面有一定的优越性。     

时变信道下基于有效容量的OFDMA系统资源分配方案

该文给出时变信道下多用户正交频分多址接入(OFDMA)系统的有效容量表达式。为了最大化系统平均有效容量,该文利用泰勒近似得到了渐近可达的多用户调度准则,根据用户移动速度、业务时延敏感特性和有效容量的关系调度用户。仿真结果表明,该方案能够更好地提高移动用户有效容量。     

OFDMA系统跨层资源分配算法

OFDM具有高频谱利用率和抗多径衰落的优点,已被公认为第三代移动通信系统长期演进标准以及第四代移动通信系统的核心技术。OFDMA是基于OFDM的一种多用户接入技术,在OFDMA系统中,各用户在不同的子载波上同时传输数据。主要研究了OFDMA系统中的跨层资源分配算法。详细分析了保证速率比例公平的非实时业务跨层资源分配算法,仿真结果说明该算法能够较好地保证用户之间的公平性,并能够获得较大的系统吞吐量和较小的业务延时。     

两跳中继OFDMA蜂窝网络下行链路呼叫阻塞率分析

本文首先提出了一种分析OFDMA蜂窝网络下行链路呼叫阻塞率的方法,在此基础上进一步分析了加入两跳中继的OFDMA蜂窝网络呼叫阻塞率.OFDMA蜂窝网络的每个呼叫接入都需要随机数量的子载波来满足用户传输速率的需求,传统GSM及CDMA网络的容量分析方法不能应用到OFDMA网络系统中.本文根据用户对子载波的需求量,把接入用户分成不同的服务类型,以多维马尔可夫链为数学模型分别分析传统和两跳中继OFDMA蜂窝网络下行链路呼叫阻塞率,最终通过数值计算分析各种参数对系统性能的影响,数值分析结果表明加入中继后的两跳中继OFDMA蜂窝网络下行链路容量比传统网络有显著的提升.     

一种OFDMA实时子载波分配算法及仿真

正交频分多址(OFDMA)是以OFDM调制为基础的新一代无线接入技术,在这种方式中,多址是通过给每个用户分配可用子载波总数的一部分来实现的。介绍了一种OFDMA下行链路的实时动态子载波分配算法,算法根据各个子载波对各个用户的瞬时信道增益,在使系统总的发送功率最小的准则下,为各用户分配最优的子载波组。最后用MATLAB语言仿真实现了该算法.仿真结果表明该算法性能要优于传统的静态子信道方案。     

认知OFDM系统中针对视频业务用户的资源分配方案

在多用户认知无线电OFDM系统中,针对实时视频业务用户,本文提出一种计算复杂度低的资源分配方案。该方案采用鱼群算法分配子载波,并提出简单功率干扰(Simple Power Interference, SPI)约束功率分配算法。目标是在满足总功率预算并且保证不干扰主用户的前提下,最大化系统的下行系统容量。仿真分析表明,在视频业务用户场景中,本文所提算法能有效提高下行系统速率,性能接近最优且复杂度低。     

OFDMA Femtocell网络中混合接入方式下的资源分配策略

Femtocell(飞小区)能够有效加强室内覆盖和系统容量。混合接入(hybrid access)方式可以兼顾授权用户和非授权用户的业务体验。针对下行混合接入方式下的正交频分复用接入(OFDMA) Femtocell网络,该文提出带权重的比例公平(WPF)调度算法,为不同类型的用户提供不同的调度权重。该文提出两种算法确定用户的调度权重,一种是自适应权重的比例公平算法,实时调整调度权重;另一种是静态权重的比例公平算法,基于WPF调度的渐近性分析得到静态最优调度权重。仿真结果表明该文提出的两种算法均能在授权用户和非授权用户间合理分配资源,保证不同用户的速率需求。     

OFDMA系统随机服务模型及呼叫接纳控制策略的研究

该文在分析OFDMA系统容量的基础上,提出了适用于自适应OFDMA系统的随机服务模型,即M| M| m| n马尔可夫排队模型,根据这个模型,我们提出了基于系统吞吐量和用户QoS要求的呼叫接纳控制策略。理论分析和仿真结果表明,当系统中只有FTP业务时,M| M| m| n模型与自适应OFDMA系统的随机服务特征非常相似,应用这个模型对系统的阻塞概率和文件的服务时间进行定量分析,其结果与实际系统的性能基本吻合。     

基站协作OFDMA系统中面向混合业务的资源分配

基站协作是多小区OFDMA系统中抑制共信道干扰、提高系统容量的有效手段。如何分配无线资源以实现资源与业务最佳匹配是基站协作OFDMA系统中的关键问题。现有的研究大多面向单一业务。该文研究了尽力而为(BE)与有速率约束(RC)两类典型业务共存情况下的子载波与功率分配问题,提出了一种两阶段的启发式算法。算法的第1阶段仅为RC用户分配资源,通过引入子载波价值矩阵,最小化满足RC用户速率约束所需的子载波数;第2阶段将剩余子载波分配给BE用户以最大化他们的和速率。仿真结果表明,所提算法在系统中断概率及BE用户和速率两项指标上均优于已有方法。     

认知OFDM系统中针对视频业务用户的资源分配

在多用户认知无线电OFDM系统中,针对实时视频业务用户,提出一种计算复杂度低的资源分配方案.该方案采用鱼群算法分配子载波,并提出简单功率干扰(Simple Power Interference,SPI)约束功率分配算法.目标是在满足总功率预算并且保证不干扰主用户的前提下,最大化系统的下行系统容量.仿真分析表明,在视频业务用户场景中,所提算法能有效提高下行系统速率,性能接近最优且复杂度低.     

A Low Complexity Resource Allocation Method for OFDMA System Based on Channel Gain

In orthogonal frequency division with multiple access (OFDMA) systems dynamic radio resource allocation improves overall performance by exploiting the multiuser diversity gains. A key issue in OFDMA is the allocation of the OFDM subcarriers and power among users sharing the channel. This paper proposes a new rate adaptive resource allocation scheme in the OFDMA downlink transmission system. Our proposed algorithm is based on the users’ sensitivity to the subcarrier allocation which means how frequency selective is the channel from the user’s perspective. As a result of frequency selectivity of the channel, different subchannels of the same user experience different levels of fade. However, how different they undergo fading could be measured by difference between maximum and minimum channel gain of that user. Our proposed method is based on difference between maximum channel gain and minimum channel gain for each user and uniform distribution of power among subcarriers. Simulation results show that the proposed algorithm achieves higher capacity over fixed TDMA method, and reported suboptimal methods with acceptable rate proportionality.     

Bee colony optimization aided adaptive resource allocation in OFDMA systems with proportional rate constraints

Orthogonal frequency division multiple access (OFDMA) is a promising technique, which can provide high downlink capacity for the emerging wireless systems. The total capacity of OFDMA can be maximized by adaptively assigning subcarriers to the users with the best gains for those subcarriers, with power subsequently distributed by water-filling. In this paper, we propose the use of artificial bee colony (ABC) algorithm combined with Deb’s selection mechanism to handle the constraints. In this scheme, a probabilistic selection scheme assigns probability values to feasible solutions based on their fitness values and to infeasible individuals based on their violations, to allocate the resources to the users in downlink OFDMA system. Specifically we propose two approaches for resource allocation in downlink OFDMA systems using ABC algorithm. In the first approach, ABC algorithm is used for subcarrier allocation only, while in second approach the ABC algorithm is used for joint subcarrier and power allocation. It is shown that both these approaches obtain higher sum capacities as compared to that obtained by previous works, with comparable computational complexity. It is also shown that the joint subcarrier and power allocation approach provides near optimal results at the cost of slightly higher computational cost.     

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.     

认知无线电下行链路中的频谱共享算法

该文提出了一种适用于下行认知无线电系统的频谱共享算法,在保证对授权用户的干扰低于限制和总发射功率受限的条件下最大化系统总容量。分析了对授权用户的干扰并给出设置干扰限制的方法,在此基础上分两步实现总容量的最大化:先通过最大信道信干噪比原则实现最优的子载波分配;然后利用提出的双注水方法计算最优的功率分配。仿真结果表明,相比传统的频谱共享算法,该算法可以获得显著的系统容量增益。     

OFDMA分布式无线接入网络中基于共享标准的资源分布研究

Distributed radio access network (DRAN) is a novel wireless access architecture and can solve the problem of the available spectrum scarcity in wireless communications. In this paper, we investigate resource allocation for the downlink of OFDMA DRAN. Unlike previous exclusive criterion based algorithms that allocate each subcarrier to only one user in the system, the proposed algorithms are based on shared criterion that allow each subcarrier to be allocated to multiple users through different antennas and to only one user through same antenna. First, an adaptive resource allocation algorithm based on shared criterion is proposed to maximize total system rate under each user’s minimal rate and each antenna’s maximal power constraints. Then we improve the above algorithm by considering the influence of the resource allocation scheme on single user. The simulation results show that the shared criterion based algorithm provide much higher total system rate than that of the exclusive criterion based algorithm at the expense of the outage performance and the fairness, while the improved algorithm based on shared criterion can achieve a good tradeoff performance.     

A Simple Superposition Coding Scheme for Optimizing Resource Allocation in Downlink OFDMA Systems

In this paper, we propose to apply a simple superposition coding strategy for downlink of OFDMA systems. The novelty of this paper consists on allowing at most two users to share the same subchannel. The main idea is to consider the subchannels allocated to the users with the weakest link, and allow these subchannels to be shared by some potential users who can transmit some number of bits with only a small amount of power. To decrease the overhead of the proposed OFDMA system, we restrict to use a predetermined superposition encoding|decoding scheme. We address the problem of resource allocation, which consists on finding the optimal subchannel assignment in the OFDMA system. A low complexity algorithm, denoted Share Specific Subcarrier Allocation (SSSA) is then proposed. It offers a fairness allocation among users. This can be done by taking into account all user’s buffer states information. Simulation results confirm that the proposed technique outperforms the classical algorithms in terms of total throughput and dropping probability.     

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.     

基于goodput优化的OFDMA系统资源分配算法

资源分配是OFDMA系统资源调度中的一个重要研究问题。针对OFDMA下行链路信道知识获取的现实误差问题,提出了一种基于实际吞吐量优化的资源分配算法。重点研究了功率和数据率在用户之间的分配问题,以往的很多分配算法通常是假设下行链路发射端具有理想信道信息,这与实际状况不符,同时根据部分信道信息得到的速率分配不被真实的信道支持,会造成传输的中断事件。算法考虑了信道估计的误差问题,将实际吞吐量goodput作为分配算法优化的依据。仿真结果表明,该算法获得了较好的多用户分集增益和实际吞吐量性能。     

Channel and queue aware joint relay selection and resource allocation for MISO-OFDMA based user-relay assisted cellular networks

User-relay assisted orthogonal frequency division multiple access (OFDMA) networks are cost-effective solutions to meet the growing capacity and coverage demands of the next generation cellular networks. These networks can be used with multiple antennas technology in order to obtain a diversity gain to combat signal fading and to obtain more capacity gain without increasing the bandwidth or transmit power. Efficient relay selection and resource allocation are crucial in such a multi-user, multi-relay and multi-antenna environment to fully exploit the benefits of the combination of user-relaying and multiple antennas technology. Thus, we propose a channel and queue aware joint relay selection and resource allocation algorithm for multiple-input single-output (MISO)-OFDMA based user-relay assisted downlink cellular networks. Since, the proposed algorithm is not only channel but also queue-aware, the system resources are allocated efficiently among the users. The proposed algorithm for the MISO-OFDMA based user-relay assisted scheme is compared to existing MISO-OFDMA based non-relaying and fixed relay assisted schemes and it is also compared with the existing single-input single-output (SISO)-OFDMA based user-relay assisted scheme. Simulation results revealed that the proposed scheme outperforms the existing schemes in terms of cell-edge users’ total data rate, average backlog and average delay.