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。     

OFDM系统中的一种新的比特功率分配算法

针对自适应OFDM系统中满足用户QoS(这里主要指用户带宽及误码率这两个指标)要求的比特功率分配这一问题,提出了一种新的算法,该算法以每次比特分配时,使得每比特(一次可分配多比特信息)的功率代价最小为原则,获得了良好的性能,仿真结果表明,该算法在满足用户QoS要求的情况下,其发射总功率比现有的同类算法小,性能更佳。摘要     

MIMO-OFDM系统一种新的自适应资源分配算法

OFDM技术、MIMO技术和自适应调制技术的结合可以有效地抗无线信道的各种衰落,最大限度提高系统的容量和传输质量,针对自适应MIMO—OFDM系统中满足用户QoS（这里主要指用户带宽及误码率这两个指标）要求的比特功率分配这一问题,提出了一种新的变步长（M—P）算法。该算法以每比特分配时,使得每比特（一次可分配偶数比特）的功率代价最小为原则,获得良好的性能。仿真结果表明：该算法在满足用户QoS要求的情况下,其发射总功率比现有的Hughes—Hartogs算法小,性能更佳。     

一种用于CDMA反向链路的公共速率控制算法

该文从实际应用角度出发,提出了一种改进的CDMA系统反向链路公共速率控制算法。在该算法中,分组数据业务移动台根据外环功率控制设置点的变化以及反向激活比特依概率控制其自身速率提高或降低。文中对概率取值进行了分析研究并构造了一种复杂度较低的次优解。经过系统级仿真,并与已有的基于反向激活比特的速率控制算法相比较,各项结果显示了改进后的算法能够保持用户服务质量(Quality of Service, QoS),并从一定程度上提高了系统吞吐量和资源利用率。     

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。     

基于信道编码的MIMO-OFDM非迭代自适应资源分配算法

 针对空时编码级联波束形成的MIMO-OFDM系统,研究了考虑信道编码的自适应传输方案。本文首先从编码增益的角度出发,利用统计信道状态信息,推导了保证用户QoS星座距离的表达式;然后证明了研究的优化问题是凸规划问题,并根据库恩-塔克条件推出了最优功率和比特加载的封闭形式解;最后提出了一种非迭代的自适应资源分配算法。仿真结果表明,本文提出算法在保证用户QoS的情况下,能够有效逼近系统吞吐量的理论值,同时该算法具有计算复杂度低的特点,可以满足实时通信的要求;并且采用LDPC码的码率越低,系统吞吐量越大。     

非线性条件下多用户OFDM系统的自适应资源分配

为了提高多用户正交频分复用(OFDM)系统的容量和功率效率，可以根据用户的服务质量(QoS)采用一种自适应的子载波、比特和功率的分配策略。然而这样使得OFDM信号更易于受非线性的影响，使用户的信噪比下降，导致QoS得不到满足。本文将研究非线性对用户最终信噪比的影响，并提出一种在这样的系统中保证用户QoS的资源分配算法，使总发射功率最小。文章最后使用该算法进行仿真，分析非线性对系统性能的影响。     

MIMO-OFDM系统中基于效用函数的跨层资源分配算法

针对多业务MIMO-OFDM系统的下行链路提出了一种基于效用函数的跨层资源分配算法.建立了以效用函数最大化为目的的跨层优化目标,分别设计了语音、流媒体和"尽力而为"三种业务的边界效用函数.算法首先在所有用户中分配子载波,然后进行单用户和空间子信道的功率、比特分配,并对比特数目进行取整处理.仿真结果表明算法满足了多种业务的QoS要求,对时延敏感的业务能提供更小的时延,同时对"尽力而为"业务提供了更高的吞吐量.     

CR系统中基于微分博弈的功率控制算法

该文针对认知无线电系统动态性的特点,将微分博弈理论应用在认知无线电系统的功率控制中,建立了功率控制的非合作微分博弈模型,提出了一种基于微分博弈的分布式非合作功率控制算法。该算法在满足认知用户平均功率门限和QoS需求的基础上,实现了分布式动态功率控制,获得了反馈纳什均衡解析解。仿真结果表明,该算法可有效控制各认知用户的发射功率,增加系统吞吐量,提高系统性能。     

多业务DS-CDMA系统的资源分配算法研究

针对提出的业务模型，分析了多业务DS-CDMA系统中各类业务的QoS性能如平均延时、吞吐量及比特差错率等与各类业务的处理增益和功率分配的关系，提出了一种适用于两类业务（一类实时、一类可靠）的优化处理增益和功率分配算法，数据结果表明优化算法可以在保证两类业务QOS的同时提高系统容量及可靠业务的吞吐量。     

OFDMA系统下行链路自适应带宽与子载波分配方案

该文分析了OFDMA系统下行链路自适应资源分配问题,在系统总功率约束下提出了最小化系统中断概率的次最佳两步子载波分配算法。首先分析用户带宽分配与子载波功率分配特点,在此基础上提出了根据系统可用资源、用户QoS要求及信道状态为用户分配带宽和子载波的两步分配算法。仿真结果表明,该文提出的算法能在极小化系统中断概率的同时满足总功率约束。     

An Efficient Adaptive Modulation Scheme for Wireless OFDM Systems

An adaptive modulation scheme is presented for multiuser orthogonal frequency‐division multiplexing systems. The aim of the scheme is to minimize the total transmit power with a constraint on the transmission rate for users, assuming knowledge of the instantaneous channel gains for all users using a combined bit‐loading and subcarrier allocation algorithm. The subcarrier allocation algorithm identifies the appropriate assignment of subcarriers to the users, while the bit‐loading algorithm determines the number of bits given to each subcarrier. The proposed bit‐loading algorithm is derived from the geometric progression of the additional transmission power required by the subcarriers and the arithmetic‐geometric means inequality. This algorithm has a simple procedure and low computational complexity. A heuristic approach is also used for the subcarrier allocation algorithm, providing a trade‐off between complexity and performance. Numerical results demonstrate that the proposed algorithms provide comparable performance with existing algorithms with low computational cost.     

Cross-layer resource allocation for QoS guarantee with finite queue constraint in multirate OFDMA wireless networks

Efficient radio resource allocation is essential to provide quality of service （QoS） for wireless networks. In this article, a cross-layer resource allocation scheme is presented with the objective of maximizing system throughput, while providing guaranteed QoS for users. With the assumption of a finite queue for arrival packets, the proposed scheme dynamically a/locates radio resources based on user＇s channel characteristic and QoS metrics derived from a queuing model, which considers a packet arrival process modeled by discrete Markov modulated Poisson process （dMMPP）, and a multirate transmission scheme achieved through adaptive modulation. The cross-layer resource allocation scheme operates over two steps. Specifically, the amount of bandwidth allocated to each user is first derived from a queuing analytical model, and then the algorithm finds the best subcarrier assignment for users. Simulation results show that the proposed scheme maximizes the system throughput while guaranteeing QoS for users.     

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.     

Resource allocation algorithm for LTE networks using fuzzy based adaptive priority and effective bandwidth estimation

In this paper, we propose a scheme to allocate resource blocks for the Long Term Evolution (LTE) downlink based on the estimation of the effective bandwidths of traffic flows, where users’ priorities are adaptively computed using fuzzy logic. The effective bandwidth of each user traffic flow that is estimated through the parameters of the adaptive β-Multifractal Wavelet Mode modeling, is used to attain their quality of service (QoS) parameters. The proposed allocation scheme aims to guarantee the QoS parameters of users respecting the constraints of modulation and code schemes (modulation and coding scheme) of the LTE downlink transmission. The proposed algorithm considers the average channel quality and the adaptive estimation of effective bandwidth to decide about the scheduling of available radio resources. The efficiency of the proposed scheme is verified through simulations and compared to other algorithms in the literature in terms of parameters such as: system throughput, required data rate not provided, fairness index, data loss rate and network delay.     

Power Allocation with Max–Min and Min–Max Fairness for Cognitive Radio Networks with Imperfect CSI

This paper consider the power allocation strategies in the cognitive radio (CR) system in the presence of channel estimation errors. As the user has different channel condition in CR systems, different amount of power resource is required to meets the QoS request. In order to guarantee the fairness of each CR user, ensure the interference from the primary user and other CR users meet the QoS requirement of the CR user and limit the interference that is caused by CR users on primary user within the range into the level that primary user can tolerate, we proposed some new power allocation schemes. The targets are to minimize the maximum power allocated to CR users, to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all CR users and to minimize the maximum outage probability over all CR users. The first power allocation scheme can be formulated using Geometric Programming (GP). Since GP problem is equivalent to the convex optimization problem, we can obtain the optimal solutions for the first scheme. The latter two power allocation schemes are not GP problems. We propose iterative algorithms to solve them. Simulation results show that proposed schemes can efficiently guarantee the fairness of CR users under the QoS constraint of the primary user and CR users.     

Design of a fair bandwidth allocation policy for VBR traffic in ATMnetworks

Since real-time variable bit rate (VBR) traffic is inherently bursty, dynamic bandwidth allocation is necessary for ATM streams that carry VBR traffic. In order to provide quality-of-services (QoS) guarantees and to reduce the computational complexity, an hybrid of guaranteed and dynamic adaptive allocation scheme requires to be implemented. Typical dynamic allocations to competing streams are done in the form of linear proportions to the bandwidth requirements. We show that during temporary link congestion such proportional arrangements can give rise to unequal queue growth and, subsequently, degraded QoS. This is found to be true even for streams that belong to the same VBR class and share identical long term traffic characteristics and QoS requirements. In this paper, four allocation algorithms are presented and analyzed in terms of their fairness and QoS potential for real-time VBR traffic. We propose and show that a novel allocation strategy, termed Minmax, solves the mentioned problem of unfairness within a class. By maintaining a fair distribution of buffer length across the streams of a class, the proposed policy can achieve better and fairer QoS performance compared to the traditional methods. We present analytical results, proofs and a simulation study of the described algorithms. Four allocation policies for handling MPEG VBR video streams are simulated in the context of a wireless ATM (WATM) medium access control. The results show that in certain scenarios, the Minmax strategy can reduce losses by an order of magnitude, while decreasing delays substantially     

Adaptive Self-Learning Resource Allocation Scheme for Unlicensed Users in High-Rate UWB Systems

In this paper, we investigate a dynamic sub-band allocation for spectrum sharing in the multiuser OFDM-UWB systems while respecting the system constraints and the distributed MAC architecture. The contribution of this work is twofold: first we propose a dynamic spectrum allocation scheme based on an analytical study by deriving a multiuser optimization problem to find the optimal allocation solution. Based on an adaptive and low-complexity approach, the proposed scheme shares the available resources among unlicensed UWB users while taking into consideration the QoS requirements and the channel conditions. Then we extend the proposed scheme to allow the coexistence of a maximum number of secondary users in one channel while maintaining all the constraints support. This leads to a time-frequency allocation approach that exploits information laying in different layers, allowing a cross-layer design. This new approach improves the system performance compared to WiMedia solution and offers a considerable gain for users that have strict QoS requirements.     

Loading Schemes for Downlink OFDMA Systems

In this paper we study the subcarrier and bit allocation strategies for downlink OFDMA system.Our opti-mization objective is to find optimum subcarrier and bit assignment minimizing the total transmitted power with the con-straints on BER and data rate for all users.We divide this problem into three steps:resource allocation,subcarrier assign-ment and single-user power and bit allocation.For the first two steps we propose new algorithms.Various loading schemesconstitute by combining these algorithms as well as algorithms proposed in Ref.[6].Simulation results demonstrate thatour proposed suboptimal loading scheme can achieve performance closer to the near optimal algorithm in Ref.[8]withmuch lower complexity than schemes in Ref.[6].