Fair Multiuser Channel Allocation for OFDMA Networks Using Nash Bargaining Solutions and Coalitions

In this paper, a fair scheme to allocate subcarrier, rate, and power for multiuser orthogonal frequency-division multiple-access systems is proposed. The problem is to maximize the overall system rate, under each user's maximal power and minimal rate constraints, while considering the fairness among users. The approach considers a new fairness criterion, which is a generalized proportional fairness based on Nash bargaining solutions and coalitions. First, a two-user algorithm is developed to bargain subcarrier usage between two users. Then a multiuser bargaining algorithm is developed based on optimal coalition pairs among users. The simulation results show that the proposed algorithms not only provide fair resource allocation among users, but also have a comparable overall system rate with the scheme maximizing the total rate without considering fairness. They also have much higher rates than that of the scheme with max-min fairness. Moreover, the proposed iterative fast implementation has the complexity for each iteration of only$O(K^2Nlog_2 N+K^4)$, where$N$is the number of subcarriers and$K$is the number of users.     

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.     

Nash bargaining solution based joint time‐frequency‐code‐power resource management algorithm for TD‐LTE systems

This paper presents a joint time‐frequency‐code‐power resource management algorithm based on the Nash bargaining solution in time‐division long term evolution systems. First, a joint radio resource allocation scheme at the time, frequency, code and power domain simultaneously is provided for the time‐division long term evolution system. Second, the proposed algorithm is modeled as a cooperative game under the constraints of each user's minimal rate requirement and available resources, for example, the maximal transmitting power. To reduce the computational complexity, the joint resource allocation algorithm is divided into time‐frequency‐code and power domain resource allocation. Also, we could approach the Pareto optimal rate as closely as possible by iterations. Simulation results show that compared with the other resource allocation algorithms, the proposed algorithm has achieved a good tradeoff between the overall system throughput and fairness among different users. Copyright © 2012 John Wiley & Sons, Ltd.     

改进的多用户OFDM系统子载波和比特分配算法

针对多用户正交频分复用（OFDM）系统资源分配问题,提出了一种改进的基于边缘自适应（MA）准则的子载波和比特分配算法。在采用比例公平准则为每个用户分配子载波集合基础上,以用户速率最大者-最小者（Max-Min）子载波交换为原则进行子载波调整,使用户功率递减同时兼顾用户的公平性;通过对信道状态信息进行判断,利用贪婪算法将用户子载波分配的比特取整,以实现系统功率最小化。实验结果表明,本文提出的改进次优算法的计算复杂度较传统分步算法稍高,但仍远低于最优算法,其系统性能得以提升,且接近最优算法。     

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.     

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.     

802．11无线局域网中AP放置与信道配置的联合算法

在多小区无线局域网规划中,接入访问点(AP)放置与信道配置是两个重要的任务。在给定用户业务需求的条件下,谋求最大系统吞吐率和资源分配的公平性是网络规划的目标,其中公平性由吞吐率均衡因子表征。在传统的规划策略中,AP放置与信道配置被分割为两个先后的步骤;而该文提出的目标函数则将这两个问题联合解决以得到更好的系统性能。当采用全局遍历时,对目标函数寻求全局最优解计算量庞大;因此该文又提出了一种有效的局部最优解搜索算法补丁算法,此算法计算量小,同时能较好地逼近全局最优解。     

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.     

On the use of immune clonal optimization for joint subcarrier and power allocation in OFDMA with proportional fairness rate

Resource allocation in orthogonal frequency division multiple access is a constraint optimization problem. In this paper, we concentrate on maximizing both the sum capacity and proportional fairness rate among users. The optimization model of resource allocation is formulated and then an immune clonalbased algorithm is proposed for it. The resource allocation is solved by separating the subcarrier and power allocation in two steps. Suitable immune operators are designed, such as clonal, mutation, Baldwin learning, selection and so on. Experiments show that, compared with the previous methods, the proposed algorithm obtains higher sum capacity with comparable computational complexity, and keeps the proportional rate more fairly among users. Copyright © 2012 John Wiley & Sons, Ltd.     

多用户MISO系统下行链路的自适应用户选择算法

针对多用户多输入单输出(MISO)系统中的用户选择问题,该文基于多用户系统的容量公式提出一种低复杂度的自适应用户选择算法,使选择的用户数随当前的信道状态自适应变化以最大化所有用户的和速率。仿真结果表明,该算法具有接近最优的性能。在此基础上结合比例公平调度对算法进行改进以保证系统中用户服务的公平性。     

NOMA增强型D2D通信的资源分配算法

传统蜂窝网络中,多址接入技术起着尤为关键的作用,与正交多址（Orthogonal Multiple Access,OMA）技术相比,非正交多址（Non-Orthogonal Multiple Access,NOMA）能够支持的用户数量远远超过可用正交资源的数量,可以达到更高的频谱效率和用户公平性。因此,为提高异构蜂窝网络的整体容量,本文研究了NOMA增强型设备到设备（Device to Device,D2D）的资源分配问题,并将其分解为两个独立的子问题:信道分配和功率控制。一方面,基于Coalition博弈为D2D组分配合适的信道;另一方面,对D2D发送功率和功率分配因子依据可行解域进行联合优化,以最大化整个网络中D2D可实现速率。仿真结果表明所提算法在保证系统性能的同时,还可以有效降低计算复杂度。      

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.     

Cross‐Layer Resource Allocation in Multi‐interface Multi‐channel Wireless Multi‐hop Networks

In this paper, an analytical framework is proposed for the optimization of network performance through joint congestion control, channel allocation, rate allocation, power control, scheduling, and routing with the consideration of fairness in multi‐channel wireless multi‐hop networks. More specifically, the framework models the network by a generalized network utility maximization (NUM) problem under an elastic link data rate and power constraints. Using the dual decomposition technique, the NUM problem is decomposed into four subproblems — flow control; next‐hop routing; rate allocation and scheduling; power control; and channel allocation — and finally solved by a low‐complexity distributed method. Simulation results show that the proposed distributed algorithm significantly improves the network throughput and energy efficiency compared with previous algorithms.     

Queue-Aware Resource Allocation for Multi-cell OFDMA Systems with QoS Provisioning

This paper proposes a queue-aware resource allocation algorithm which provides quality of service (QoS) guarantees. The proposed solution adopts a cross-layer design approach since it is aware of both users’ queue buffer states (data link layer) and channel quality state (physical layer). Main advantages of the proposed resource allocation algorithm are: the low computational complexity and its capacity of maintaining lower QoS violation probability than other multi-cellular schemes. The proposed solution can also result in enhanced cell-edge data rate and improved fairness performance. User minimum data rate and target bit error rate as considered as QoS parameters. Validation of the proposed algorithm is achieved through various simulation scenarios wherein QoS violation probability, system fairness, user average data rate and cell-edge throughput are investigated. Numerical results and complexity analysis demonstrate the efficiency and the feasibility of the proposed QoS-oriented approach.     

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.     

非线性能量收集下的鲁棒性波束赋形

在无线信息能量同步传输系统中,考虑实际电路实现中的非线性能量收集模型,提出了一种具有鲁棒性的波束赋形设计方案。为了提升系统用户间的公平性,对最小的用户信干噪比进行优化,并构建了一个非凸的优化问题。针对问题的非凸特性以及引入信道估计误差带来的限制条件,基于S过程对问题进行变形,并通过半定松弛技术对问题进行凸化,提出了一种基于二分法的迭代波束赋形算法。仿真结果表明,相比于非鲁棒性算法,所提的算法能够获得25%到50%的性能增益。因此,所提算法更加适用于实际系统中的非理想信道环境。仿真结果还表明所提算法相比于线性能量收集模型或迫零波束赋形等方法,能够取得更好的公平性能。      

鱼群算法在多用户OFDM跨层资源分配中的应用

基于人工鱼群算法,利用已知信道信息对多用OFDM系统中的资源进行跨层分配.本文提出了新的目标函数,合理有效地找到了总传输速率最大化和实现用户的速率要求、比例公平要求的权衡点.为了减小资源分配的复杂度,本文提出首先对子载波进行分配,然后进行功率分配.仿真结果表明,人工鱼群算法的很好的解决了多用户OFDM系统中的跨层资源分...     

Fairness based resource allocation for multiuser MISO-OFDMA systems with beamforming

Resource allocation problem in multiuser multiple input single output-orthogonal frequency division multiple access (MISO-OFDMA) systems with downlink beamforming for frequency selective fading channels is studied. The article aims at maximizing system throughput with the constraints of total power and bit error rate (BER) while supporting fairness among users. The downlink proportional fairness (PF) scheduling problem is reformulated as a maximization of the sum of logarithmic user data rate. From necessary conditions on optimality obtained analytically by Karush-Kuhn-Tucker (KKT) condition, an efficient user selection and resource allocation algorithm is proposed. The computer simulations reveal that the proposed algorithm achieves tradeoff between system throughput and fairness among users.     

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 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.