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.     

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。      

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.     

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].     

Joint overlay and underlay resource allocation with weighted fairness in OFDM‐based cognitive radio systems

In this paper, the problem of hybrid overlay and underlay spectrum access is investigated for OFDM‐based cognitive radio (CR) systems. Both the metrics for system (e.g. capacity) and users (e.g. fairness) are integrated into the unified framework of weighted‐capacity maximization with the interference constraint in CR systems. For easing the procedure of resource allocation, two criteria, respectively, for subcarrier assignment and power allocation are theoretically derived based on the Karush–Kuhn–Tucker conditions. Under the guidance of the two criteria, max‐capacity subcarrier assignment and optimal power allocation are proposed to flexibly distribute spectrum resources to secondary users. In order to reduce the computational complexity further, a suboptimal power allocation algorithm, referred to as cap‐limited waterfilling, is also presented by decomposing the interference constraint. Simulation results show that the capacity and fairness performance of the proposed algorithms is considerably better than the conventional ones in references. The proposed suboptimal algorithm with substantially lower complexity approaches to optimal power allocation in the vicinity of only 1% performance gap. Meanwhile, joint access model is greatly beneficial to spectrum efficiency enhancement in CR systems. Copyright © 2014 John Wiley & Sons, Ltd.     

协作系统中基于比例公平的资源分配方法

针对多用户协作中继系统中的资源分配问题,提出了一种在满足用户速率比例公平约束条件下的新算法。该算法先将由2个时隙组成的中继用户传输链路转换为一个等效信道链路,将涉及子载波分配、中继选择和功率分配的组合优化问题转化为分步的次优化问题。该算法在等功率分配情况下,根据各用户速率比例公平系数进行初步子载波数目分配;以瞬时信道增益最佳原则,进行剩余子载波数目分配及具体子载波分配,同时完成中继选择;在速率比例公平约束条件下推导出次优化功率分配的闭式表达式,从而完成各子载波上的功率分配。仿真结果表明,该算法在有效提高系统容量的同时,保证了各用户速率之间的比例公平性。     

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.     

Power saving for real-time services in multiuser OFDMA-based cognitive radio systems under average interference constraint

This paper considers a power minimization problem for Quality-of-Service provisioning in the downlink of multiuser OFDMA-based cognitive radio systems with real-time services by jointly optimizing over subcarrier and power allocation. An average interference constraint is imposed to protect the primary transmission. The optimal solution is obtained by using Lagrange methods. It can be seen that the optimal power allocation follows a modified water-filling approach with different water levels for different subcarriers and users. An optimal algorithm and a suboptimal algorithm based on stochastic nature are then proposed. Numerical comparisons show that the performance of the suboptimal algorithm with low complexity is close to that of the optimal one, which demonstrate that the suboptimal algorithm outperforms other algorithms.     

多用户OFDM系统的次最优分配算法

本文提出了一种多用户OFDM系统中次最优的自适应载波、比特和能量分配算法。此算法利用各子载波的瞬时特性,在保证各个用户服务质量(QoS)的前提下,通过合理地分配子载波并调整各个子载波调制等级,达到降低总发射功率的目的。该算法相对于最优算法具有简单、公平、高效的特点。仿真实验表明,该算法的性能接近最优算法。     

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.     

Dynamic resource allocation algorithm in multi-user cooperative OFDMA systems: considering QoS and fairness constraints

Wireless transmission systems are constrained by several parameters such as the available spectrum bandwidth, mobile battery energy, transmission channel impairments and users’ minimum quality-of-service. In this paper, a new strategy is investigated that aims at improving the allocation of resources in a dual hop OFDMA cooperative network consisting in multi source–destination pairs and multiple decode-and-forward relays. First, the joint optimization of three types of resources: power, sub-channel and relay nodes, is formulated as a problem of subchannel-relay assignment and power allocation, with the objective of minimizing overall transmission power under the bit-error-rate and data rate constraints. However, the optimal solution to the optimization problem is computationally complex to obtain and may be unfair. Assuming knowledge of the instantaneous channel gains for all links in the entire network, an iterative three-step resource allocation algorithm with low complexity is proposed. In order to guarantee the fairness of users, several fairness criteria are also proposed to provide attractive trade-offs between network performance (i.e. overall transmission power, average network lifetime and average outage probability) and fairness to all users. Numerical studies are conducted to evaluate the performance of the proposed algorithm in two practical scenarios. Simulation results show that the proposed allocation algorithm achieves an efficient trade-off between network performance and fairness among users.     

An effective suboptimal power loading scheme in OFDM-based cognitive radio systems

Orthogonal frequency division multiplexing (OFDM) is an attractive modulation candidate for Cognitive Radio (CR) networks. Effective and reliable subcarrier power allocation in OFDM-based Cognitive Radio (CR) networks is a challenging problem. This paper focuses on the power allocation for OFDM-based Cognitive Radio (CR) networks. Our objective is to maximize the total transmission rates of Secondary Users (SU) by adjusting the power of subcarrier while the interference introduced to the Primary User (PU) is within a certain range and the total power of subcarrier is not beyond the total power constraint. We investigate the optimal power allocation algorithm for OFDM-based Cognitive Radio (CR) based on convex optimization theory. Then, because of high complexity of the optimal power allocation algorithm, we propose an effective suboptimal power loading scheme. Theory analysis and simulation results show that the performance of the suboptimal power allocation algorithm is close to the performance of the optimal power allocation algorithm, while the complexity of the suboptimal power allocation algorithm is much lower.     

Chunk‐based and fairness‐based resource allocation in multicast distributed MISO‐OFDMA systems

The resource allocation problem for the downlink of orthogonal frequency‐division multiple access (OFDMA) wireless multicast systems is investigated. It is assumed that the base station consists of multiple antennas in a distributed antenna system (DAS), whereas each user is equipped with a single antenna. The multicasting technology is able to support several groups of users with flexible quality of service (QoS) requirements. The general mathematical formulation is provided, but achieving the optimal solution has a high computational cost. In our approach, the allocation unit is not the subcarrier, as in conventional OFDMA systems, but a set of contiguous subcarriers, which is called ‘chunk’. For practical implementation, a suboptimal but efficient algorithm is proposed in order to maximize the sum of the maximum attainable data rates of multicast groups of users, subject to total available power and proportional maximum attainable data rate constraints among multicast groups of users. Simulation and complexity analyses are provided to support the benefits of chunk‐based resource allocation to multicast OFDMA DASs, supporting that the proposed algorithm can be applied to latest‐generation wireless systems that provide QoS guarantees. Copyright © 2013 John Wiley & Sons, Ltd.     

OFDMA中继通信系统中非对称的资源分配

传统的OFDMA协作通信系统,中继经过一一对应的两跳子载波接收和发送数据信息,这一对称的资源分配模式限制了系统吞吐量的提高;本文放宽对称约束,研究了非对称模式下的资源分配问题。自由度的增加,增大了系统资源分配的复杂度,这是一个结合中继选择、子载波分配和功率控制等多维自由度的混合离散型优化问题,很难得到满足实时性要求的近似最优算法。针对该模型,本文提出基于拉格朗日松弛的联合优化算法,算法的关键在于OFDMA系统的渐进强对偶性,这个性质使得多项式时间算法的设计成为可能。算法的复杂度与子载波数目成线性关系。仿真结果表明,该算法的性能是近似最优的,而且与对称模式相比,非对称模式下的资源分配进一步提升了系统的吞吐量性能。      

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.     

Resource Allocation Algorithm for Multi‐cell Cognitive Radio Networks with Imperfect Spectrum Sensing and Proportional Fairness

This paper addresses the resource allocation (RA) problem in multi‐cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered—such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP‐hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub‐gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.     

A Resource Allocator for the Uplink of Multi-Cell OFDMA Systems

We propose a simple distributed radio resource allocation algorithm for an OFDMA cellular system, which aims at minimizing the overall transmitted power subject to a rate constraint for each user. In order to reduce the problem complexity we use a single modulation; simulations show that the resulting performance degradation is negligible when the number of users is high enough. Moreover, we propose a simple distributed heuristic that, by reducing the rate constraints, steers the multicell system towards an stable resource allocation. Results show that the proposed system exhibits a great robustness to the destructive effects of multiple access interference.     

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.     

Resource allocation in MIMO‐OFDM‐based cooperative cognitive radio networks: optimal and suboptimal low complexity approaches

The problem of resources allocation in multiple‐input multiple‐output‐orthogonal frequency division multiplexing based cooperative cognitive radio networks is considered, in this paper. The cooperation strategy between the secondary users is decode‐and‐forward (DF) strategy. In order to obtain an optimal subcarrier pairing, relay selection and power allocation in the system, the dual decomposition technique is recruited. The optimal resource allocation is realized under the individual power constraints in source and relays so that the sum rate is maximized while the interference induced to the primary system is kept below a pre‐specified interference temperature limit. Moreover, because of the high computational complexity of the optimal approach, a suboptimal algorithm is further proposed. The jointly allocation of the resources in suboptimal algorithm is carried out taking into account the channel qualities, the DF cooperation strategy, the interference induced to the primary system and the individual power budgets. The performance of the different approaches and the impact of the constraint values and deploying multiple antennas at users are discussed through the numerical simulation results. Copyright © 2014 John Wiley & Sons, Ltd.     

基于不完美CSI的低轨卫星通信系统鲁棒资源分配算法

为了解决低轨卫星通信系统因资源受限导致的能量与速率不平衡的问题,同时考虑信道不确定性对实际卫星通信系统性能衰退的影响,该文提出一种基于最大化最小能效的鲁棒资源分配算法。首先,考虑每个用户中断速率约束、功率分配系数约束和最大发射功率约束,基于高斯信道不确定性,构建了联合优化卫星波束成形向量与功率分配因子的鲁棒资源分配模型。所描述的问题是一个含参数摄动的非凸、非确定性多项式难问题,很难直接求解。为此,基于丁克尔巴赫、伯恩斯坦不等式、半正定松弛和交替优化等方法将其转化为等价的凸优化问题,并提出一种基于迭代的混合鲁棒波束成形与功率分配算法。仿真结果表明,该文算法具有较好的能效和较强的鲁棒性。