OFDMA techniques in multicellular networks with total frequency reuse

Orthogonal frequency division multiple access (OFDMA) techniques are investigated in this paper. Five subchannel allocation algorithms are analysed and their performance in a multicellular environment is evaluated with simulations. Four schemes of lower complexity, suitable for the early deployment of wireless systems, are compared with a more computationally demanding scheme with respect to their blocking probability, loading factor and offered bit rate. The channel condition of each carrier is calculated and its knowledge is used for power controlled adaptive modulation, as an essential feature of the OFDMA technique. The general radio resource management process is divided into two steps: in the first step a base station allocates carriers to users while in the second step the modulation and power levels for each allocated carrier are defined.The simulation results demonstrate that a wireless system in its early deployment phase (up to 15–30% blocking probability) can employ simple OFDMA techniques capable of achieving high throughput. Furthermore, it is demonstrated that two of the proposed lower complexity schemes, (those based on cell coordination), offer good performance gain for higher data rate services. Nevertheless, these schemes achieve relatively lower gains with adaptive modulation, when compared with the techniques which exploit interference averaging or adaptive interference mitigation.     

Competitive scheduling for OFDMA systems with guaranteed transmission rate

Next-generation broadband wireless standards use orthogonal frequency division multiple access (OFDMA) as the preferred physical layer multiple access scheme, especially for the downlink. Due to limited resources available at the base station, multi-user resource allocation is crucial for delivering the applications with various quality-of-service (QoS) demands. We study the OFDMA resource allocation problem for the adaptive modulation and coding (AMC) mode of mobile WiMAX, in which resources in the form of allocation units (AU) are to be allocated and the channel knowledge of only some good sub-channels for the users is available to the scheduler. The objective is to maximize the sum-rate for all the users while maintaining guaranteed minimum and maximum traffic rates for certain users under a total transmission power constraint. Two novel factors, band selectivity factor (BSF) and competition factor (CF), are introduced. Based on the two factors, we propose a sub-optimal approach, rate-guaranteed competitive scheduling (RCS). It is suitable to be deployed in practical systems and exploits multi-user diversity with very low complexity. Simulation results show that RCS can achieve almost 75% of throughput of the optimal solution.     

Resource allocation for physical-layer security in OFDMAdownlinkwith imperfect CSI

We investigate the problem of resource allocation in a downlink orthogonal frequency-division multiple access (OFDMA) broadband network with an eavesdropper under the condition that both legitimate users and the eavesdropper are with imperfect channel state information (CSI). We consider three kinds of imperfect CSI: (1) noise and channel estimation errors, (2) feedback delay and channel prediction, and (3) limited feedback channel capacity, where quantized CSI is studied using rate-distortion theory because it can be used to establish an informationtheoretic lower bound on the capacity of the feedback channel. The problem is formulated as joint power and subcarrier allocation to optimize the maximum-minimum (max-min) fairness criterion over the users’ secrecy rate. The problem considered is a mixed integer nonlinear programming problem. To reduce the complexity, we propose a two-step suboptimal algorithm that separately performs power and subcarrier allocation. For a given subcarrier assignment, optimal power allocation is achieved by developing an algorithm of polynomial computational complexity. Numerical results show that our proposed algorithm can approximate the optimal solution.     

Satisfying demands in a multicellular network: A universal power allocation algorithm

Power allocation to satisfy user demands, in the presence of large number of interferers (in a multicellular network), is a challenging task. Further, the power to be allocated depends upon the system architecture, for example upon components like coding, modulation, transmit precoder, rate allocation algorithms, available knowledge of the interfering channels, etc. This calls for an algorithm via which each base station in the network can simultaneously allocate power to their respective users so as to meet their demands (whenever they are within the achievable limits), using whatever information is available of the other users. The goal of our research is to propose one such algorithm which in fact is universal: the proposed algorithm works from a fully co-operative setting to almost no co-operation and or for any configuration of modulation, rate allocation, etc. schemes. The algorithm asymptotically satisfies the user demands, running simultaneously and independently within a given total power budget at each base station. Further, it requires minimal information to achieve this: every base station needs to know its own users demands, its total power constraint and the transmission rates allocated to its users in every time slot. We formulate the power allocation problem in a system specific game theoretic setting, define system specific capacity region and analyze the proposed algorithm using ordinary differential equation (ODE) framework. Simulations further confirm the effectiveness of the proposed algorithm. We also demonstrate the tracking abilities of the algorithm.     

Iterative power and subcarrier allocation in rate-constrained orthogonal multicarrier downlink systems based on hybrid harmony search heuristics

This paper presents a novel iterative hybrid algorithm for subcarrier and power allocation in a cognitive orthogonal frequency division multiple access (OFDMA) downlink. In the considered setup a primary base station forwards information to K distant receivers by using a single OFDM waveform, whereas a secondary base station - subject to stringent per-user rate constraints - interferes with the former by sending information from users to the same set of destinations. Power and user allocation at both base stations is jointly performed by the proposed algorithm to maximize the overall throughput of the setup while satisfying, at the same time, the imposed rate constraints. Our proposal, which stems from an hybridization of the harmony search (HS) and differential evolution (DE) algorithms along with a greedy local repair method, is shown - through computer simulations over the extended vehicular A ITU channel model - to be an effective and practical resource allocation procedure for cognitive OFDMA downlinks.     

一种容量最大化的OFDMA资源分配算法

针对功率受限的多用户OFDMA系统,提出了一种简化的子载波和功率分配算法,此算法在最大化系统容量的同时兼顾了用户间的公平性。算法首先依据当前的信道状况计算出各用户所需的载波数量,并分配子载波,然后以注水算法对各载波上的功率进行分配。仿真结果表明,以此算法对OFDMA的系统资源进行分配可显著提高系统的多项性能。     

Optimal user scheduling and power control in multi-user cognitive broadcast systems

Cognitive radio systems should not only have the ability to sense and exploit "frequency spectrum holes",but also the ability to sense and utilize "spatial spectrum holes".In this paper,we consider the issue of maximizing the throughput of the cognitive systems by fully utilizing "spatial spectrum holes" brought in by multiple cognitive users,in the scenario where a pair of licensed users and a cognitive broadcast system share multiple spectrum bands.By exploiting the channel reciprocity under the premise that the licensed system adopts the time-division-duplexing (TDD) mode,we propose a more practical cognitive access scheme that can sense the interference at the licensed user caused by the cognitive transmitter,based on the existing feedback signals from the licensed user to the licensed base station.Taking both interferences from the licensed base station to the cognitive receiver and from the cognitive transmitter to the licensed user into consideration,we investigate the optimal user scheduling and power allocation scheme that can maximize the ergodic sum rate of the cognitive system.We show that scheduling the user whose channel gain to interference and noise ratio (CGINR) is the largest for each frequency band is optimal.We also derive the dynamic power allocation scheme meeting the three practical constraints,i.e.,the transmitter’s average transmission power constraint,the power amplifier’s instantaneous transmission power constraint,and the interference power constraint at the licensed user.The result shows that in different coherent time intervals and different frequency bands,the power allocation has a multi-level waterfilling structure.Theoretical analysis shows that the strategy scheduling user with the largest CGINR introduces significant performance improvement compared with the traditional strategy scheduling user with the largest channel gain to noise ratio (CGNR).We also illustrate the impact of power constraints and the number of users on system performance by simulation.     

基于角度域的FDD大规模MIMO系统开销优化

针对信道信息获取中导频开销与反馈开销过大的问题,研究了FDD大规模MIMO系统的开销优化。基于信道角度域大尺度参数的多样性,引入成簇多径信道模型,设计了一种角度域的开销优化方案。在此方案中,通过广播预先设计的预编码码本和用户强度反馈,在基站侧建立角度域的拓扑关系,进行整体用户调度与预编码码本分配。在典型仿真场景下,与传统方案相比,系统开销平均减少60%,系统和速率平均提升35%。通过角度域的码本匹配,有效减少了系统开销,提升了系统性能。     

电力线通信系统中跨层的用户调度和资源分配

针对多用户多业务基于正交频分多址的电力线通信系统,提出一种在数据链路控制层进行用户调度和在物理层进行资源分配的多层多目标最优的跨层资源分配算法,其用户调度根据所有用户的服务质量(QoS)满意程度、QoS要求、业务包模型、信道状态信息和队列状态信息,从所有用户中选出要服务的用户和确定这些用户的最优跨层参数;其资源分配则根据所有调度用户的QoS要求、最优跨层参数和信道状态信息,先把功率按地窖注水原理分给每个子载波,再把每个子载波最优地分给调度用户并采用逐比特加载查表算法调整其上分配的功率和比特。最后在典型的电力线信道环境下对算法进行仿真,结果表明新算法在系统资源大范围变化时也能保障用户的服务质量,同时有效地提高系统资源的利用。     

一种多用户MIMO系统中有限反馈预编码算法及性能分析

多用户多输入多输出(MIMO)系统中,用户可以通过反馈的方式把信道状态信息(CSI)传递给基站,基站利用该CSI进行预编码或者用户调度,可以有效地提取复用增益。但是传统的反馈方式,反馈量太大,占用过多上行资源。针对收发都是多天线条件的多用户MIMO系统,提出一种基于Grassmannian码本的有限反馈预编码方法,通过对用户信道矩阵进行量化,每个用户仅仅需要反馈一个序号而不是信道矩阵,从而大大减少了反馈量。通过对系统误码率(BER)和吞吐率的仿真,表明了该方法能保证系统性能。同时,由于信道估计存在误差,量化过程存在误差,所以,分析了信道矩阵误差对于新方法性能的影响,得到了系统吞吐率同信道矩阵误差的方差,以及基站发射功率三者的关系,并通过仿真进行验证,从而为评估信道估计和量化过程的优劣提供了理论依据。     

Optimal admission control algorithms for scheduling burst data in CDMA multimedia systems

The third generation mobile communication systems are widely envisioned to be based on wideband code division multiple access (CDMA) technologies to support high data rate (HDR) packet data services. To effectively harness the precious bandwidth while satisfying the HDR requests from users, it is crucial to use a judicious burst admission control algorithm. In this paper, we propose and evaluate the performance of a novel jointly adaptive burst admission algorithm, called the synergistic burst admission control algorithm to allocate valuable resources (i.e., channels) in wideband CDMA systems to burst HDR requests. We consider the spatial dimension only, and by that we mean the algorithm performs scheduling and admission control, for the current frame only, based solely on the selection diversity in the geographical and mobility aspects. The scheduler does not exploit the temporal dimension in that it does not make allocation decisions about future frames (i.e., requests that do not get allocation are simply ignored and such requests will be treated as new request in future frames). In the physical layer, we use a variable rate channel-adaptive modulation and coding system which offers variable throughput depending on the instantaneous channel condition. In the MAC layer, we use the proposed optimal multiple-burst admission algorithm, induced by our novel integer programming formulation of the admission control and scheduling problem. We demonstrate that synergy could be attained by interactions between the adaptive physical layer and the burst admission layer. Both the forward link and the reverse link burst requests are considered and the system is evaluated by dynamic simulations which takes into account of the user mobility, power control and soft handoff. We found that significant performance improvement, in terms of average packet delay, data user capacity and coverage, could be achieved by our scheme compared to the existing burst assignment algorithms.     

Performance prediction for OFDMA systems with dynamic power and subcarrier allocation

It is well known that channel-dependent OFDMA resource assignment algorithms provide a significant performance improvement compared to static (i.e., channel-unaware) approaches. Such dynamic algorithms constantly adapt resource assignments to current channel states according to some objective function. Due to these dynamics, it is difficult to predict the resulting performance for such schemes given a certain scenario (characterized by the number of terminals in the cell and their average channel gains). In this paper we provide a novel, analytical framework for performance prediction, which takes dynamic power and subcarrier allocation into account. The analysis is based on fundamental transformations of the channel gains caused by the dynamic subcarrier allocations. This insight allows for deriving probability functions of the achieved rate per subcarrier which ultimately yields expressions for the expected minimal rates as well as outage probabilities for certain rate demands. Hence, the methods presented in this paper for performance prediction can be employed for admission control in systems with dynamic resource allocation. We illustrate the applicability of our derivations with respect to the capacity of 802.16e systems for Voice-over-IP and video streams. The results demonstrate a significant improvement compared to state-of-the art approaches but also reveal room for improvement of this approach compared to the optimal system performance.     

WiMAX技术中OFDMA上行链路载波频偏补偿算法研究*

在OFDMA上行链路中,由于多个用户的载波频率偏差（CFO）破坏了载波间的正交性,从而在基站接收端产生多用户间干扰（MUI）。针对这个问题提出了一种能够实现载波频偏补偿的低复杂度迭代信号处理算法。仿真结果表明,这种算法能有效消除MUI,改善了WiMAX上行链路的传输性能。     

一种多用户OFDMA比例公平资源分配算法

针对多用户OFDMA系统资源分配中已有算法对系统容量和公平性兼顾较差的情况,提出了一种满足比例公平性的系统容量最大化资源分配算法。首先选择合适的公平度门限范围,在子载波分配中,先将各个子载波分配给信道增益最大的用户,再在公平度门限约束下重新分配最大速率用户的信道增益最小的子载波,可以实现子载波利用率和公平度的折中。然后采用注水线法分配功率来调整用户间的比例公平性,最终找到使系统容量最大的公平度门限。仿真结果表明,该算法在保证了用户间比例公平性为1的同时提高了系统容量。     

QoS-aware bandwidth allocation and admission control in IEEE 802.16 broadband wireless access networks: A non-cooperative game theoretic approach

In this paper, we propose an adaptive bandwidth allocation and admission control mechanism based on game theory for IEEE 802.16 broadband wireless networks. A non-cooperative two-person non-zero-sum game is formulated where the base station and a new connection are the players of this game. The solution of the game formulation provides not only the decision on accepting or rejecting a connection, but also the amount of bandwidth allocated to a new connection (if admitted). A queueing model considering adaptive modulation and coding in the physical layer is used to analyze quality of service (QoS) performances, namely, the delay performance for real-time and the throughput performance for non-real-time polling services and best effort service. This queueing model is used by the proposed bandwidth allocation and admission control mechanism to ensure that the utilities for both the base station and the new connection are maximized. The performance of the proposed scheme is evaluated by simulation and compared with that of each of the traditional admission control with static and adaptive bandwidth allocation schemes.     

MU-MIMO系统中利用信道信息预测值的反馈机制

提出了一种多用户MIMO下行链路中基于收发双方共同预测信道的信道信息反馈机制。在实际传输时,基站和用户双方采用相同的算法预测信道,用户将信道预测值和真实值之差,通过离线设计好的LBG码本进行量化,将码本序号反馈给基站。该方案中,利用实测的大样本信道采样值,以均值意义下的预测误差最小化为目标,采用LBG算法设计了量化码本。基站根据用户反馈的码本序号和自己实时的信道预测值,重建出接近真实信道的估计值,并利用该估计值对传输数据做预编码。仿真结果验证了所提方法的有效性。     

OFDMA认知无线电网络中面向功率控制的频谱定价与分配

针对OFDMA认知无线电网络,提出一种基于Stackelberg博弈的频谱定价和分配模型.对于次基站控制次网络传输功率来保护主网络通信的场景,主基站可通过该模型获得最优的频谱定价方案.从功率控制的角度,重新设计次用户的效用函数,运用Stackelberg博弈对单个主基站和多个次用户在频谱租赁市场中的交易行为进行建模.通过逆向归纳法,求解市场均衡下的最优频谱定价,使得主基站在考虑主网络QoS降级的同时获得最大收益.此外,对于主基站只能获取本地信息的情形,提出了基于动态Stackelberg博弈的分布式频谱定价和分配模型.仿真实验表明,该模型能够在控制次网络传输功率的基础上,提供最优频谱定价和频谱分配方案.     

一种多天线多用户大规模MIMO上行系统能效资源分配算法

针对目前大规模MIMO系统的资源分配研究集中于用户终端配备单天线的场景,但随着技术的发展和用户需求的增长,用户智能终端配备多天线情形越来越多,提出一种基于多天线多用户大规模MIMO上行系统的能效资源分配算法。在满足用户速率和续航要求的条件,基站采用迫零(ZF)接收情况下,通过建立系统能效函数,采用凸优化方法进行优化。首先确定用户不同天线的最优发射功率,再运用二分法确定基站激活的天线数目,通过联合用户发射功率和激活基站天线数来优化系统能效。仿真结果表明本文所提算法可以在迭代次数较少的情况下取得较好的系统能效。     

基于OFDMA系统的改进型功率分配贪婪算法研究

通过考虑功率分配中OFDMA系统的吞吐量与用户间公平性能的平衡问题,在公平约束条件下,提出一种改进型功率分配贪婪算法.该算法根据用户请求进行子载波的预分配,可以有效地实现每个用户具体的比特分配和功率分配.仿真结果表明,该算法的吞吐量逼近于迭代注水功率分配算法,可以在OFDMA系统的吞吐量与用户间的公平性能之间寻求到一个理想的平衡点.     

A weighted cooperative spectrum sensing framework for infrastructure-based cognitive radio networks

Spectrum sensing plays a critical role in cognitive radio networks. A good sensing scheme can reduce the false alarm probability and the miss detection probability, and thus improves spectrum utilization. This paper presents a weighted cooperative spectrum sensing framework for infrastructure-based cognitive radio networks, to increase the spectrum sensing accuracy. The framework contains two modules. In the first module, each cognitive radio performs local spectrum sensing and computes the total error probability, which combines the false alarm probability and the miss detection probability. The total error probability and the energy signal from the primary user are then sent to the base station. In the second module, the base station makes a final decision after combining the weighted energy signals from all cognitive radios. The final decision is then broadcasted back to all cognitive radios. To reduce the computation complexity and communication overhead, the base station also instructs the cognitive radios that have large total error probabilities not to report their local sensing results. We have developed a theoretical model for the proposed framework, and derived the optimal detection threshold, as well as the minimum number of cognitive radios required to participate in cooperative sensing, subject to a given total error probability. Numerical results verify that the proposed weighted cooperative spectrum sensing framework significantly improves the sensing accuracy.