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.     

Proportional-fair energy-efficient radio resource allocation for OFDMA smallcell networks

This paper investigates the energy-efficient radio resource allocation problem of the uplink smallcell networks. Different from the existing literatures which focus on improving the energy efficiency (EE) or providing fairness measured by data rates, this paper aims to provide fairness guarantee in terms of EE and achieve EE-based proportional fairness among all users in smallcell networks. Specifically, EE-based global proportional fairness utility optimization problem is formulated, taking into account each user’s quality of service, and the cross-tier interference limitation to ensure the macrocell transmission. Instead of dealing with the problem in forms of sum of logarithms directly, the problem is transformed into a form of sum of ratios firstly. Then, a two-step scheme which solves the subchannel and power allocation separately is adopted, and the corresponding subchannel allocation algorithm and power allocation algorithm are devised, respectively. The subchannel allocation algorithm is heuristic, but can achieve close-to-optimal performance with much lower complexity. The power allocation scheme is optimal, and is derived based on a novel method which can solve the sum of ratios problems efficiently. Numerical results verify the effectiveness of the proposed algorithms, especially the capability of EE fairness provisioning. Specifically, it is suggested that the proposed algorithms can improve the fairness level among smallcell users by 150–400 % compared to the existing algorithms.     

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.     

多无人机辅助通信中用户匹配与频谱资源联合优化方法

针对多无人机作为空中基站为地面设备提供临时服务的动态频谱分配问题，主要考虑无人机与地面用户匹配、子信道分配和功率分配三个方面。为了保证用户通信的公平性，在考虑频谱复用和共信道干扰的情况下，以最大化地面用户最小传输速率为目标，提出了一种用户匹配与频谱资源联合优化算法来解决上述混合整数非线性优化问题，通过聚类算法优化无人机与地面用户的最佳匹配，通过块坐标下降法迭代优化子信道分配和功率分配。仿真实验分析表明，提出的求解方法可以有效提升用户的传输速率，保证用户通信公平性。     

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.     

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.     

Resource allocation based on dynamic hybrid overlay/underlay for heterogeneous services of cognitive radio networks

In cognitive radio networks (CRNs), hybrid overlay and underlay sharing transmission mode is an effective technique to improve the efficiency of radio spectrum. Unlike existing works in literatures where only one secondary user (SU) uses both overlay and underlay mode, the different transmission modes should dynamically be allocated to different SUs according to their different quality of services (QoS) to achieve the maximal efficiency of radio spectrum. However, dynamic sharing mode allocation for heterogeneous services is still a great challenge in CNRs. In this paper, we propose a new resource allocation method based on dynamic allocation hybrid sharing transmission mode of overlay and underlay (Dy-HySOU) to obtain extra spectrum resource for SUs without interfering with the primary users. We formulate the Dy-HySOU resource allocation problem as a mixed-integer programming to optimize the total system throughput with simultaneous heterogeneous QoS guarantee. To decrease the algorithm complexity, we divide the problem into two sub-problems: subchannel allocation and power allocation. Cutset is used to achieve the optimal subchannel allocation, and the optimal power allocation is obtained by Lagrangian dual function decomposition and subgradient algorithm. Simulation results show that the proposed algorithm further improves spectrum utilization with simultaneous fairness guarantee, and the achieved Dy-HySOU diversity gain is satisfying.     

多天线OFDM系统中的自适应子信道分配和天线选择

针对多用户MIMO-OFDM系统,提出自适应子信道分配算法.首先将相邻的子载波分块成若干子信道,在分配子信道的时候优先考虑平均信道容量小的用户,并且将相对利用度大的子信道分配给该用户,从而在频谱利用率和公平性上具有较好的性能.为了降低发送端的硬件复杂度以及非线性因素的影响,将自适应信道分配和发送天线选择相结合,提出联合自适应子信道分配和天线选择算法.仿真结果表明,本文提出的联合算法具有较高的频谱效率和较低的中断概率.     

基于保密度的OFDMA中继网络资源分配研究

考虑到异构双向中继网络中存在窃听者的安全资源分配问题,为了提高中继安全性,该文研究了受限于子信道分配和功率约束的用户安全保密度问题模型,与传统的保密容量模型相比,安全保密度模型更侧重于反映用户本身的安全程度。基于此保密度模型,该文进一步考虑了不同用户的安全服务质量(Quality of Service, QoS)需求和网络公平性,联合优化功率分配、子信道分配、子载波配对,并分别通过约束型粒子群、二进制约束型粒子群优化算法和经典的匈牙利算法找到最优解,实现资源的最优分配,提高网络中合法用户的保密度。仿真结果验证了所提算法的有效性。     

一种基于多小区OFDMA系统用户公平性约束的分布式资源分配算法

针对多小区OFDMA系统下行链路,研究了用户公平性约束下的资源分配问题,提出了一种多基站协作的迭代优化的分布式资源分配算法。每个小区根据干扰状况及用户公平性,迭代地进行子载波和功率的资源优化;而每次迭代中,根据用户公平性准则分配子载波,并将非凸的小区功率优化问题转化为其下界的凸问题,通过一个分布式算法来求解。通过仿真验证了算法的有效性;仿真结果表明,与传统网络的固定功率分配的情形相比,所提算法保证了用户之间的公平性并显著提高了系统吞吐量。     

优化公平性的多用户OFDM系统下行链路资源分配算法

研究了优化公平性的多用户OFDM系统下行链路的资源分配算法,根据系统各用户的业务需求,在保证用户所得数据速率满足一定比例以及系统总功率限制的前提下,提高系统总数据速率。首先,根据公平性原则进行用户的子载波分配,子载波功率分配使用注水算法;子载波分配完成后,利用贪婪功率分配算法,以最大化用户数据速率和提高功率利用率为目标,对各用户内部子载波功率和比特数进行再分配。仿真结果表明,相比参考文献[10]的算法,该算法在提高系统总速率的同时,更好地保证了用户数据速率的公平性;相比参考文献[12]的算法,该算法虽然牺牲了一定的系统总速率,但能提供更高的用户数据速率公平性。     

基于比例公平原则的多用户MIMO-OFDM系统资源分配

提出了一种基于比例公平原则提高MIMO-OFDM系统吞吐量的子载波和功率分配算法.它在总功率和误比特率的约束下,以获取最大系统吞吐量为目标,同时为兼顾用户间资源享用的公平性,根据用户速率成比例推导出了子载波分配限制准则.仿真结果表明,本算法不仅可满足不同用户的速率要求,而且平衡了容量最大化和用户间公平性的矛盾,同时计算...     

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.     

Optimal Uplink Power Control in Two-Cell Systems with Rise-over-Thermal Constraints

Joint assignment of transmit powers to users through basestation cooperation improves system capacity. In this letter, we study the optimal power allocation for sum capacity in a two-cell system with an individual rise-over-thermal constraint per basestation. It is proven that the optimal power allocation to any pair of users resides in one of five discrete power assignments, each of which corresponds to at least one constraint being binding. We propose a joint proportional fairness scheduler across two cells that extends the optimal power allocation to multi-user systems. Simulations show that the combined power allocation and proportional fairness scheduler achieves significant gains over a conventional round-robin scheduler, in terms of both cell average and cell edge throughput.     

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.     

Joint subchannel and power allocation in multiuser OFDM systems with minimal rate constraints

In this paper, we study the adaptive resource allocation in multiuser orthogonal frequency division multiplexing (OFDM) systems. We try to maximize the sum capacity of an OFDM system with given transmission power budget, while meeting users' minimal rate requirements. Unlike other resource allocation schemes, which generally separate subchannel allocation and power distribution into independent procedures, our proposed algorithm implements joint subchannel and power allocation. Given a set of subchannels, the required power to satisfy a user's minimal rate constraint is calculated by water‐filling policy. Then, the user who requires the maximum power to meet the rate requirement has a priority to obtain an additional subchannel. The procedure continues until all subchannels are consumed, by which time the consumed power to meet all users' rate requirements is also worked out. Finally, the margin power is allocated among all subchannels in an optimal manner to maximize the sum capacity of the OFDM system. Simulation results show that our proposed algorithm performs better than other existing ones. The solution produced by our proposed algorithm is close to the upper bound, while its complexity is relatively lower compared with other methods, which makes it attractive for applications. Copyright © 2012 John Wiley & Sons, Ltd.     

多用户MIMO-OFDM系统中的子信道与功率分配算法研究

针对多用户MIMO-OFDM系统下行链路,分析了通过遍历搜索来使容量最大化的最优子信道与功率分配算法,在此基础上提出了低复杂度的次优多用户子信道与功率分配算法,即MSPA算法。为了最大限度地保证用户之间的公平性,进一步提出了考虑每个用户速率要求的MSPA-RoU算法。仿真结果表明：本文提出的MSPA算法在复杂度可接受的情况下所获得的容量增益与最优算法十分接近,并且远远大于在MIMO环境下仅对子载波进行分配的算法;MSPA-RoU算法在考虑用户速率要求时仍能获得可观的容量增益。     

多用户OFDM系统中一种新颖的自适应功率分配方案

针对多用户正交频分复用(OFDM)系统自适应资源分配的问题,提出了一种新的自适应子载波分配方案。子载波分配中首先通过松弛用户速率比例约束条件确定每个用户的子载波数量,然后对总功率在所有子载波间均等分配的前提下,按照最小比例速率用户优先选择子载波的方式实现子载波的分配;在功率分配中提出了一种基于人工蜂群算法和模拟退火算法(ABC-SA)相结合的新功率分配方案,并且通过ABC-SA算法的全局搜索实现了在所有用户之间的功率寻优,同时利用等功率的分配方式在每个用户下进行子载波间的功率分配,最终实现系统容量的最大化。仿真结果表明,与其他方案相比,所提方案在兼顾用户公平性的同时还能有效地提高系统的吞吐量,进而证明了所提方案的有效性。     

认知型飞蜂窝网络中的子信道分配与功率控制

为了解决宏蜂窝与飞蜂窝构成的两层异构网络上行干扰与资源分配问题,提出了一种在认知型飞蜂窝的双层异构网中结合子信道分配和功率控制进行资源分配的框架。通过对异构网中跨层干扰问题进行分析与建模,将求解最优子信道分配矩阵和用户发射功率矩阵作为干扰管理问题的解决方法。模型中认知型飞蜂窝网络子信道和飞蜂窝网络用户构成非合作博弈,双方利用效用函数最优值进行匹配,构成初始信道分配矩阵;再由接入控制器根据接入条件从初始信道分配矩阵中筛选用户,并优化接入用户的发射功率矩阵,得到最优子信道分配矩阵和功率矩阵。仿真结果表明,优化框架提高了双层异构网络中飞蜂窝网络用户的吞吐量和接入率,降低了异构网中跨层干扰。     

VLC网络中兼具功率与时隙分配的自适应干扰管理机制

为了更好解决目前可见光通信（visible light communication,VLC）中干扰管理方案存在的动态优化问题,提出了一种兼具优化功率分配与时隙分配的自适应干扰管理机制。首先,在每个时隙依据用户的位置建立每个用户的接入点（access point,AP）协作集,寻找所有由最多数量互不干扰用户组成的极大独立集,以此自适应地避免同频干扰;在每个时隙为每个极大独立集采用改进的线性注水功率分配算法为信道自适应地分配发送功率,以此优化每个极大独立集的用户和速率;基于用户和速率、速率公平性及时延公平性的归一化优先因子,选出具有最大优先因子的候选极大独立集,其中包含的用户在该时隙被调用。通过仿真且与代表性文献中的算法比较可得,本文提出的自适应干扰管理与优化资源分配方案在网络频谱利用率、能效、用户速率公平性与时延公平性方面具有明显优势。