Dynamic Resource Allocation in OFDMA-Based DF Cooperative Relay Networks

This paper investigates the Resource allocation problem in OFDMA-based decode-and-forward cooperative communication systems. The objective is to maximize the sum throughput under the constraints of joint total transmission power and subchannels occupation, while maintaining the maximum fairness among multiple relay nodes. Since the optimal solution to this combinatorial problem is extremely computationally complex to obtain, we propose a low-complexity suboptimal algorithm that allocates subchannel and power separately. In the proposed algorithm, subchannel allocation over the relay nodes is first performed under the assumption of equal power distribution. Then, an optimal power allocation algorithm named multi-level water-filling is used to maximize the sum rate. The simulation results show that the performance of the proposed algorithm can approach asymptotically to that of the optimal algorithm while enhancing the fairness among all relay nodes and reducing computational complexity from exponential to linear with the number of subchannels. It is also shown that the proposed equal power distribution algorithm with subchannel permutation (SP) outperforms the one without SP.     

An efficient data rate maximization algorithm for OFDM based wireless networks

In this paper we present a computationally efficient, suboptimal integer bit allocation algorithm that maximizes the overall data rate in multiuser orthogonal frequency division multiplexing (OFDM) systems implemented in wireless networks. Assuming the complete knowledge of a channel and allowing a subchannel to be simultaneously shared by multiple users we have solved this data rate maximization problem in two steps. The first step provides subchannel assignment to users considering the users’ requests on quality of service (QoS) expressed as the minimum signal-to-noise ratio (SNR) on each subchannel. The second step provides transmit power and bit allocation to subchannels in order to maximize the overall data rate. To reduce computational complexity of the problem we propose a simple method which assigns subchannels to users and distributes power and bits among them. We have analyzed the performance of our proposed algorithm by simulation in a multiuser frequency selective fading environment for various signal-to-noise ratios and various numbers of users in the system. We have concluded that our algorithm, unlike other similar algorithms, is suitable for OFDM wireless networks, especially when signal-to-noise ratio in the channel is low. Also, the results have shown that the total data rate grows with the number of users in the system.     

Resource allocation for multiuser cognitive OFDM networks with proportional rate constraints

In this paper we study the resource allocation problem for the multiuser orthogonal frequency division multiplexing (OFDM)‐based cognitive radio (CR) systems with proportional rate constraints. The mutual interference introduced by primary user (PU) and cognitive radio user (also referred to secondary user, SU) makes the optimization problem of CR systems more complex. Moreover, the interference introduced to PUs must be kept under a given threshold. In this paper, the highest achievable rate of each OFDM subchannel is calculated by jointly considering the channel gain and interference level. First, a subchannel is assigned to the SU with the highest achievable rate. The remaining subchannels are always allocated to the SU that suffers the severest unjustness. Second, an efficient bit allocation algorithm is developed to maximize the sum capacity, which is again based on the highest achievable rate of each subchannel. Finally, an adjustment procedure is designed to maintain proportional fairness. Simulation results show that the proposed algorithm maximizes the sum capacity while keeping the proportional rate constraints satisfied. The algorithm exhibits a good tradeoff between sum capacity maximization and proportional fairness. Furthermore, the proposed algorithm has lower complexity compared with other algorithms, rendering it promising for practical applications. Copyright © 2011 John Wiley & Sons, Ltd.     

OFDMA中继网络基于效用的资源分配

研究半双工正交频分复用（OFDMA）中继网络的资源分配。解决动态子信道分配,自适应功率分配,传输策略选择和中继选择的联合优化问题。为了公平利用中继用户的资源,把中继用户所能帮助的最大子信道数和每个子信道的功率设为常量。在此基础上,提出贪婪算法以最大化总效用。当算法每次分配资源时,把资源分配给潜在效用增长最大的用户。仿真结果表明所提算法与固定的资源分配策略相比,能更高效地利用资源,并且改善了用户间的公平性。     

Resource allocation with proportional rate fairness in orthogonal frequency division multiple access relay networks

We address the problem of subchannel and transmission power allocation in orthogonal frequency division multiple access relay networks with an aim to maximize the sum rate and maintain proportional rate fairness among users. Because the formulated problem is a mixed‐integer nonlinear optimization problem with an extremely high computational complexity, we propose a low‐complexity suboptimal algorithm, which is a two‐step separated subchannel and power allocation algorithm. In the first step, subchannels are allocated to each user, whereas in the second step, the optimal power allocation is carried out on the basis of the given subchannel allocation and the nonlinear interval Gauss–Seidel method. Simulation results have demonstrated that the proposed algorithm can achieve a good trade‐off between the efficiency and the fairness compared with two other existing relevant algorithms. In particular, the proposed algorithm can always achieve 100% fairness under various conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

速率比例公平下多用户OFDM系统的自适应资源分配

在多用户正交频分复用(MU-OFDM)系统中,考虑各个用户之间具有比例数据传输速率限制条件下的一种公平的自适应资源分配方案的最优算法计算量巨大,为此,提出了一种将子信道分配和功率分配相分离的次优算法.首先,在假设相同功率分配的情况下进行子信道的分配,然后在保持一定比例公平条件下使总容量最大时进行最优功率分配.对该算法的仿真表明,在用户数为2、子信道数为10的系统中,所提算法的容量性能接近最优算法,而计算量由指数增长变为线性增长.所提资源分配算法的总容量比以前的算法在用户间的分配更公平也更灵活.     

Adaptive resource allocation in multiuser OFDM systems with proportional rate constraints

Multiuser orthogonal frequency division multiplexing (MU-OFDM) is a promising technique for achieving high downlink capacities in future cellular and wireless local area network (LAN) systems. The sum capacity of MU-OFDM is maximized when each subchannel is assigned to the user with the best channel-to-noise ratio for that subchannel, with power subsequently distributed by water-filling. However, fairness among the users cannot generally be achieved with such a scheme. In this paper, a set of proportional fairness constraints is imposed to assure that each user can achieve a required data rate, as in a system with quality of service guarantees. Since the optimal solution to the constrained fairness problem is extremely computationally complex to obtain, a low-complexity suboptimal algorithm that separates subchannel allocation and power allocation is proposed. In the proposed algorithm, subchannel allocation is first performed by assuming an equal power distribution. An optimal power allocation algorithm then maximizes the sum capacity while maintaining proportional fairness. The proposed algorithm is shown to achieve about 95% of the optimal capacity in a two-user system, while reducing the complexity from exponential to linear in the number of subchannels. It is also shown that with the proposed resource allocation algorithm, the sum capacity is distributed more fairly and flexibly among users than the sum capacity maximization method.     

Distributed subchannel and rate assignment for multi-carrier multi-cell networks

A distributed subchannel and rate assignment (DSRA) algorithm, which integrates the subchannel allocation and the rate assignment to minimize the number of subchannels needed for meeting the rate requirements, is proposed for the multi-carrier multi-cell networks. The DSRA algorithm need not measure the channel gains and executes the distributed power control to allocate the subchannel and transmission rate. One can decrease the number of subchannels used in the DSRA algorithm by increasing the number of iterations.     

基于用户公平性的MIMO-OFDM空间子信道分配算法

对多用户"多入多出-正交频分复用"(MIMO-OFDM)系统的空间子信道分配算法进行了研究,提出了使系统吞吐量最大化并且满足用户速率最小要求的多用户无线资源调度算法.仿真结果表明,与波束形成相比.所提算法具有更好的性能,既充分利用空间子信道,提高了系统容量,又采取有效措施保障了用户的公平性.     

频率选择性衰落信道中多用户OFDM系统的自适应分配算法

本文提出一种适用于多径频率选择性衰落信道中多用户OFDM系统的自适应分配算法.算法根据信道瞬时估计值,自适应地为多用户分配子信道和传输比特数,在给定误比特率的条件下,使系统总的发送功率达到最小.作者根据时分复用的基本思想,提出多用户最佳子信道和比特分配算法,导出系统最小发送功率的下限,并在此基础上,进一步提出次佳自适应分配算法.数值模拟表明:次佳算法所需的发送功率比下限值高约1dB;与等比特分配方案相比自适应分配算法可节省功率约3-4dB;与静态信道分配方案相比,自适应分配算法可节省功率6-8dB.     

OFDM中自适应比特及功率分配的分析

在宽带移动OFDM(正交频分复用)系统中,不同的子信道经受不同的信道衰落,因此具有不同的传输能力。根据子信道的增益对子信道上加载的比特数进行自适应分配,可在满足一定误码率(BER)性能要求下使系统的总传输功率达到最小。本文研究了一种在一定传输速率下的自适应比特及功率分配算法。该算法可适用于多径频率选择性衰落信道。仿真结果表明,采用自适应技术可大大提高OFDM系统的性能。     

Joint Subchannel,Rate and Power Allocation in OFDMA-Based Cognitive Wireless Mesh Network

In this paper, the problem of resource allocation in an Orthogonal Frequency Division Multiple Access-based Cognitive Wireless Mesh Network (CWMN) is addressed. The objective is to maximize the total utilities in a CWMN, which is defined as any increasing, concave and twice differentiable function of the end-to-end flow rate, by jointly allocating each link’s rate, power and subchannels under the constraints of multiple primary users’ Interference Temperature and multiple access interference. First, a centralized resource allocation algorithm is developed based on the Column Generation approach, and shown to be optimal. So it can perform as a criterion for designing other algorithms. Secondly, considering the applicability of algorithm in distributed system, a near-optimal distributed algorithm is proposed, which allocates subchannel based on routing information at first, and then jointly allocates the resource of rate and power. Finally, the simulation results validate the centralized and distributed algorithms, and show that better performance can be achieved than the conventional algorithm.     

Adaptive subcarrier bandwidth and power in OFDM‐based cognitive radio systems for high mobility applications

OFDM‐based cognitive radio systems are spectrally flexible and efficient, but they are vulnerable to intercarrier interference (ICI), especially in high mobility environments. High mobility of the terminal causes large Doppler frequency spread resulting in serious ICI. Such ICI severely degrades the system performance, which is ignored in the existing resource allocation of OFDM‐based cognitive radio systems. In this paper, an adaptive subcarrier bandwidth along with power allocation problem in OFDM‐based cognitive radio systems for high mobility applications is investigated. This adaptive subcarrier bandwidth method should choose the suitable subcarrier bandwidth not only to balance the tradeoff between ICI and intersymbol interference but also to be large enough to tolerate an amount of Doppler frequency spread but less than the coherence bandwidth. The power budget and interference to primary users caused by cognitive radio users are imposed for primary users' protection. With these constraints, a joint optimization algorithm of subcarrier bandwidth and power allocation is proposed to maximize the bandwidth efficiency of OFDM‐based cognitive radio systems in such conditions. Numerical simulation results show that the proposed algorithm could maximize the system bandwidth efficiency and balance this tradeoff while satisfying the constraints. Copyright © 2012 John Wiley & Sons, Ltd.     

Cross-layer resource allocation for real-time services in OFDM-based cognitive radio systems

The resource allocation problem on the downlink of a multiuser OFDM-based cognitive radio (CR) system is formulated using a cross-layer (MAC and PHY layers) approach with the aim of satisfying quality of service (QoS) requirements in real-time applications. The number of subchannels available to the CR system is time-varying as a result of the stochastic nature of the activities of the primary users (PUs). The MAC layer QoS requirements are dynamically converted to PHY layer rate requirements; the conversion depends on the delivery status of queued packets as well as the number of available subchannels. Simulation results show that the proposed cross-layer resource allocation algorithm can provide substantial transmit power reductions compared to existing PHY layer and MAC layer solutions designed for multiuser OFDM systems.     

基于多用户MIMO/OFDM系统的空间子信道分配算法

对多用户MIMO/OFDM系统空间子信道进行了研究,以获取最大的系统吞吐量为目标,推导了子载波分配准则,提出了一种自适应空间子信道分配算法,并给出了相应的算法流程。仿真结果表明,该算法具有良好的性能,有效地提高了系统的传输速率。     

Clustering-based interference management in densely deployed femtocell networks

Deploying femtocells underlaying macrocells is a promising way to improve the capacity and enhance the coverage of a cellular system. However, densely deployed femtocells in urban area also give rise to intra-tier interference and cross-tier issue that should be addressed properly in order to acquire the expected performance gain. In this paper, we propose an interference management scheme based on joint clustering and resource allocation for two-tier Orthogonal Frequency Division Multiplexing (OFDM)-based femtocell networks. We formulate an optimization task with the objective of maximizing the sum throughput of the femtocell users (FUs) under the consideration of intra-tier interference mitigation, while controlling the interference to the macrocell user (MU) under its bearable threshold. The formulation problem is addressed by a two-stage procedure: femtocells clustering and resource allocation. First, disjoint femtocell clusters with dynamic sizes and numbers are generated to minimize intra-tier interference. Then each cluster is taken as a resource allocation unit to share all subchannels, followed by a fast algorithm to distribute power among these subchannels. Simulation results show that our proposed schemes can improve the throughput of the FUs with acceptable complexity.     

基于多用户MIMO-OFDM系统的子信道和功率分配算法

在多用户MIMO-OFDM系统中，当总功率受限时，为了使整个系统的数据传输速率最大．已有的最优算法的计算十分复杂，这里采用了一种次最优算法。在发射端，基于已知信道状态信息。应用奇异值分解将MIMO信道转化为并行的子信道，并将表征信道增益的信道特征值用于子信道自适应调制优化设计中。在自适应过程中．用到了子信道和功率联合分配算法。仿真结果表明，这种算法能使系统的性能明显提高。     

基于合作中继的OFDM蜂窝网络的QoS感知资源调度算法

针对基于中继的OFDM蜂窝网络,该文考虑具有不同QoS要求的混合业务场景,引入合作传输机制,提出了一种基于合作中继的QoS感知资源调度算法,解决了合作中继节点选取,子载波分配以及功率控制等问题。以最大化系统效用为目标,在考虑QoS业务的速率要求与基站功率约束的同时,针对中继结构引入了中继节点的功率约束。为降低计算复杂度,将原非线性组合优化问题分解为子载波分配与功率控制两个子问题。仿真结果表明,该文所提算法在能量节约、系统效用,吞吐量等性能方面都有显著优势。     

基于能效的NOMA蜂窝车联网动态资源分配算法

在支持车与车直接通信(V2V)的非正交多址接入(NOMA)蜂窝网络场景下,针对V2V用户与蜂窝用户的干扰以及NOMA准则下的功率分配问题,该文提出一种基于能效的动态资源分配算法。该算法首先为了保证V2V用户的时延及可靠性同时满足蜂窝用户的速率需求,联合考虑子信道调度、功率分配和拥塞控制,建立了最大化系统能效的随机优化模型。其次,利用李雅普诺夫随机优化方法,通过控制可接入数据量保证队列稳定性以避免网络拥塞,并根据实时网络负载状态动态地进行资源调度,设计一种次优化子信道匹配算法获得用户调度方案,进一步,利用凸优化理论和拉格朗日对偶分解方法得到功率分配策略。最后,仿真结果表明,该文算法可以满足不同用户的服务质量(QoS)需求,并在保证网络稳定性前提下提高系统能效。     

Adaptive proportional fairness resource allocation for OFDM-based cognitive radio networks

In this paper, we study the resource allocation problem in multiuser Orthogonal Frequency Division Multiplexing (OFDM)-based cognitive radio networks. The interference introduced to Primary Users (PUs) is fully considered, as well as a set of proportional rate constraints to ensure fairness among Secondary Users (SUs). Since it is extremely computationally complex to obtain the optimal solution because of integer constraints, we adopt a two-step method to address the formulated problem. Firstly, a heuristic subchannel assignment is developed based on the normalized capacity of each OFDM subchannel by jointly considering channel gain and the interference to PUs, which approaches a rough proportional fairness and removes the intractable integer constraints. Secondly, for a given subchannel assignment, we derive a fast optimal power distribution algorithm that has a complexity of O(L ² N) by exploiting the problem’s structure, which is much lower than standard convex optimization techniques that generally have a complexity of O((N + K)³), where N, L and K are the number of subchannels, PUs and SUs, respectively. We also develop a simple power distribution algorithm with complexity of only O(L + N), while achieving above 90 % sum capacity of the upper bound. Experiments show that our proposed algorithms work quite well in practical wireless scenarios. A significant capacity gain is obtained and the proportional fairness is satisfied perfectly.