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.     

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.     

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.     

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。     

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.     

Joint power,subcarrier and subframe allocation in Multihop relay networks

In this paper we study the problem of subframe, subchannel and power allocation in OFDMA‐based multihop relay networks. The system consists of a base station (BS), a number of relay stations (RS) and mobile stations (MS). We consider frame by frame scheduling, where the frame is divided into two subframes such as BS‐RS and RS‐MS subframes. We study two different problems, satisfying link rate requirements with minimum‐weighted total power and maximizing proportional fairness. For the first problem, we find the optimal solution and also propose a less complex subframe and bandwidth allocation scheme with good performance. For the second problem, we propose an algorithm that outperforms an existing scheme with less feedback. Copyright © 2009 John Wiley & Sons, Ltd.     

Proportional Fairness in Multi?Carrier System with Multi?Slot Frames: Upper Bound and User Multiplexing Algorithms

Optimal Proportional Fair Scheduling (PFS) in a multi-carrier system is a prohibitively complex combinatorial problem. In this paper we consider practical time frames with multiple time slots, where this optimal allocation becomes even more complex. Therefore, we derive bounds for the optimal proportional fair allocation, by means of convex optimization, and propose approximation algorithms where several users can be time-multiplexed on a same subchannel. With a much lower complexity than the optimal allocation, these algorithms achieve an excellent tradeoff between throughput and proportional fairness, even with the increased signaling overhead.     

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.     

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 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.     

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。      

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。     

Clustering‐based low‐complexity resource allocation in two‐tier femtocell networks with QoS provisioning

In this paper, we study the resource allocation problem of the uplink transmission with delay quality‐of‐service constraints in two‐tier femtocell networks. Particularly, to provide statistical delay guarantees, the effective capacity is employed as the network performance measure instead of the conventional Shannon capacity. To make the problem computationally efficient and numerically tractable, we decompose the problem into three subproblems, namely, cluster configuration subproblem, intra‐cluster subchannel allocation subproblem and inter‐cluster power control subproblem. Firstly, we develop a low‐complexity heuristic semi‐dynamic clustering scheme, where the delay of the channel state information feedback via backhaul is considered. We model such system in the framework of networked partial observation Markov decision process and derive a strategy to reduce the search range for the best cluster configuration. Then, for a given cluster configuration, the cluster heads deal with subchannel allocation and power control within each cluster. We propose a subchannel allocation scheme with proportional fairness. Thereafter, the inter‐cluster power control subproblem is modeled as a set of exact potential games, and a channel quality related pricing mechanism is presented to mitigate inter‐cluster interference. The existence and uniqueness of Nash equilibriums for the proposed game are investigated, and an effective decentralized algorithm with guaranteed convergence is designed. Simulation results demonstrate that the proposed algorithms not only have much lower computational complexity but also perform close to the exhaustive search solutions and other existing schemes. Copyright © 2015 John Wiley & Sons, Ltd.     

面向用户体验的多小区混合非正交多址接入网络资源分配方法

该文研究了多小区混合非正交多址接入(MC-hybrid NOMA)网络的资源分配。为满足异构用户的服务体验,以最大化全网综合平均意见评分(MOS)累加和为目标,考虑基站选择、信道接入和功率资源分配的联合优化问题,该文提出一种用户、基站和信道3方的2阶段转移匹配算法,并根据用户MOS进行子信道功率优化。仿真结果表明所提多小区混合NOMA网络资源分配方案能有效提升全网用户服务体验和公平性。     

Energy efficient power allocation strategy for downlink MU-MIMO with massive antennas

With the increasing energy consumption, energy efficiency （EE） has been considered as an important metric for wireless communication networks as spectrum efficiency （SE）. In this paper, EE optimization problem for downlink multi-user multiple-input multiple-output （MU-MIMO） system with massive antennas is investigated. According to the convex optimization theory, there exists a unique globally optimal power allocation achieving the optimal EE, and the closed-form of the optimal EE only related to channel state information is derived analytically. Then both the approximate and accurate power allocation algorithms with different complexity are proposed to achieve the optimal EE. Simulation results show that the optimal EE obtained by the approximate algorithm coincides to that achieved by the accurate algorithm within the controllable error limitation, and these proposed algorithms perform better than the existing equal power allocation algorithm. The optimal EE and corresponding SE increase with the number of antennas at base station, which is promising for the next generation wireless communication networks.     

QoS-based optimal and fair resource allocation for energy-efficiency uplink NOMA networks

The energy-efficiency(EE) optimization problem was studied for resource allocation in an uplink single-cell network, in which multiple mobile users with different quality of service (QoS) requirements operate under a non-orthogonal multiple access (NOMA) scheme. Firstly, a multi-user feasible power allocation region is derived as a multidimensional body that provides an efficient scheme to determine the feasibility of original channel and power assignment problem. Then, the size of feasible power allocation region was first introduced as utility function of the subchannel-user matching game in order to get high EE of the system and fairness among the users. Moreover, the power allocation optimization to the EE maximization is proved to be a monotonous decline function. The simulation results show that compared with the conventional schemes, the network connectivity of the proposed scheme is significantly enhanced and besides, for low rate massive connectivity networks, the proposed scheme obtains performance gains in the EE of the system.     

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.     

Proportional fair scheduling with superposition coding in a cellular cooperative relay system

Many works have tackled on the problem of throughput and fairness optimization in cellular cooperative relaying systems. Considering firstly a two-user relay broadcast channel, we design a scheme based on superposition coding (SC) which maximizes the achievable sum-rate under a proportional fairness constraint. Unlike most relaying schemes where users are allocated orthogonally, our scheme serves the two users simultaneously on the same time-frequency resource unit by superposing their messages into three SC layers. The optimal power allocation parameters of each SC layer are derived by analysis. Next, we consider the general multi-user case in a cellular relay system, for which we design resource allocation algorithms based on proportional fair scheduling exploiting the proposed SC-based scheme. Numerical results show that the proposed algorithms allowing simultaneous user allocation outperform conventional schedulers based on orthogonal user allocation, both in terms of throughput and proportional fairness. These results indicate promising new directions for the design of future radio resource allocation and scheduling algorithms.     

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.