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.     

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.     

User scheduling and power allocation for nonfull buffer traffic in NOMA downlink systems

Nonorthogonal multiple access (NOMA) is one of the key technologies for 5G, where the system capacity can be increased by allowing simultaneous transmission of multiple users at the same radio resource. The most of the proportional fairness (PF)–based resource allocation studies for NOMA systems assumes full buffer traffic model, while the traffic in real‐life scenarios is generally nonfull buffer. In this paper, we propose User Demand–Based Proportional Fairness (UDB‐PF) and Proportional User Satisfaction Fairness (PUSF) algorithms for user scheduling and power allocation in NOMA downlink systems when traffic demands of the users are limited and time‐varying. UDB‐PF extends the PF‐based scheduling by allocating optimum power levels towards satisfying the traffic demand constraints of user pair in each resource block. The objective of PUSF is to maximize the network‐wide user satisfaction by allocating sufficient frequency and power resources according to traffic demands of the users. In both cases, user groups are selected first to simultaneously transmit their signals at the same frequency resource, while the optimal transmission power level is assigned to each user to optimize the underlying objective function. In addition, the genetic algorithm (GA) approach is employed for user group selection to reduce the computational complexity. When the user traffic rate requirements change rapidly over time, UDB‐PF yields better sum rate (throughput) while PUSF provides better network‐wide user satisfaction results compared with the PF‐based user scheduling. We also observed that the GA‐based user group selection significantly reduced the computational load while achieving the comparable results of the exhaustive search.     

Resource allocation in downlink OFDMA distributed multipoint systems with incoherent and coherent transmitters

Distributed multipoint systems (DMS) are important and timely for the move to future broadband wireless communication systems.Traditional studies on DMS have mainly focused on the issues with the spatial division multiple access such as precoding techniques,which only consider a narrowband case.This paper addresses the downlink radio resource management of the orthogonal frequency division multiple access DMS (OFDMA-DMS),including power allocation between users or subcarriers,and distributed antenna selection.Signal models with incoherent and coherent transmitters are built.To maximize the system throughput,for the incoherent transmitter case,a strategy based on the iterative water-filling power allocation is proposed to approach the optimality.As for the coherent case,where coherent additions of the signal could occur at the users,the problem is transformed into an integer programming which is solvable.Numerical results show that the gain from the coherent transmitter is promising.And to achieve a near-optimal solution,only part of the DA ports will be used,which have better channel conditions.     

User scheduling and power allocation for downlink multi-cell multi-carrier NOMA systems

In Non-Orthogonal Multiple Access (NOMA), the best way to fully exploit the benefits of the system is the efficient resource allocation. For the NOMA power domain, the allocation of power and spectrum require solving the mixed-integer nonlinear programming NP-hard problem. In this paper, we investigate user scheduling and power allocation in Multi-Cell Multi-Carrier NOMA (MCMC-NOMA) networks. To achieve that, we consider Weighted Sum Rate Maximization (WSRM) and Weighted Sum Energy Efficiency Maximization (WSEEM) problems. First, we tackle the problem of user scheduling for fixed power using Fractional Programming (FP), the Lagrange dual method, and the decomposition method. Then, we consider Successive Pseudo-Convex Approximation (SPCA) to deal with the WSRM problem. Finally, for the WSEEM problem, SPCA is utilized to convert the problem into separable scalar problems, which can be parallelly solved. Thus, the Dinkelbach algorithm and constraints relaxation are used to characterize the closed-form solution for power allocation. Extensive simulations have been implemented to show the efficiency of the proposed framework and its superiority over other existing schemes.     

Toward the Energy Efficiency of Resource Allocation Algorithms for OFDMA Downlink MIMO Systems

The problem of the simultaneous multi-user resource allocation algorithm in orthogonal frequency division multiple access (OFDMA) based systems has recently attracted significant interest. However, most studies focus on maximizing the system throughput and spectral efficiency. As the green radio is essential in 5G and future networks, the energy efficiency becomes the major concern. In this paper, we develop four resource allocation schemes in the downlink OFDMA network and the main focus is on analyzing the energy efficiency of these schemes. Specifically, we employ the advanced multi-antenna technology in a multiple input-multiple output (MIMO) system. The first scheme is based on transmit spatial diversity (TSD), in which the vector channel with the highest gain between the base station (BTS) and specific antenna at the remote terminal (RT) is chosen for transmission. The second scheme further employs spatial multiplexing on the MIMO system to enhance the throughput. The space-division multiple-access (SDMA) scheme assigns single subcarrier simultaneously to RTs with pairwise “nearly orthogonal” spatial signatures. In the fourth scheme, we propose to design the transmit beamformers based on the zero-forcing (ZF) criterion such that the multi-user interference (MUI) is completely removed. We analyze the tradeoff between the throughput and power consumption and compare the performance of these schemes in terms of the energy efficiency.     

基于改进遗传算法的C-RAN网络动态无线资源分配

针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(Remote Radio Head,RRH)选择、子载波分配和RRH功率分配三个维度进行研究.首先,根据传统的C-RAN系统传输模型和QoS约束在时变业务环境下建立了以发射功率为变量,以吞吐量最大为优化目标的优化问题;然后,基于改进的遗传算法,将原优化方案转变为通过优化RRH选择、子载波分配和RRH功率分配来达到提高系统吞吐量的目的;最后,将改进的遗传算法与其他智能算法在种群规模变化下进行了时间复杂度对比.实验结果表明,所提算法具有较低时间复杂度,所提资源分配方案下的平均吞吐量增益为17％.     

Optimal resource allocation for energy efficiency in coordinated multicell OFDMA networks

Because energy efficiency (EE) is inevitable in future wireless cellular networks, in this paper, we focus on improving the number of bits delivered to users for each unit energy consumption in the downlink of orthogonal frequency‐division multiple access cellular networks with base stations (BSs) coordination. Specifically, each BS shares the channel qualities of users with others and jointly choose the set of co‐channel users and the transmit power allocated to maximize the EE of the system subject to the transmit power ceiling of each BS and minimum required data rate. We formulate the problem as a nonlinear fractional optimization problem, using nonlinear fractional programming, the original hard‐to‐solve problem is transferred to a new one that has the same optimal solution and is easier to solve, this enables two iterative algorithms that achieve nearly the same maximum EE. Numerical results are provided to show the convergence and superiority of the two proposed. Copyright © 2014 John Wiley & Sons, Ltd.     

多用户MIMO系统中基于快速匹配调度的有限反馈SDMA

提出了一种能高效利用多用户分集和空分复用增益的有限反馈空分多址(SDMA,space division multiple access)方法。首先利用子空间扰动的方法构造了一种具有分簇结构的多用户预编码码本。基于该码本,进一步给出了一种新型的多用户机会调度算法,该算法利用码本的簇结构实现对信道条件匹配的用户组进行快速的机会调度,同时确定被调度用户的首选码字。仿真结果表明,在蜂窝网络中,与传统的有限反馈SDMA方法相比,所提方法可以在不明显增加反馈开销的前提下显著提高系统吞吐量。     

Performance analysis of dynamic channel allocation based on the greedy approach for orthogonal frequency‐division multiple access downlink systems

This paper presents a performance analysis of dynamic channel allocation (DCA) based on the greedy approach (GA) for orthogonal frequency‐division multiple access downlink systems over Rayleigh fading channels. The GA‐based DCA achieves its performance improvement using multiuser diversity. We analyze the statistics of the number of allocable users that represents the multiuser diversity order at each allocation process. The derived statistics are then used to analyze the performance of GA‐based DCA. The analysis results show that the number of subcarriers allocated to each user must be equal to achieve the maximum system performance based on outage probability and data throughput. Copyright © 2011 John Wiley & Sons, Ltd.     

Effective resource scheduling scheme considering scheduling relevancy for downlink joint transmission system

Coordinated multi-point(CoMP) transmission is a promising technique to improve both cell average and cell edge throughput for long term evolution-advanced(LTE-A).For CoMP joint transmission(CoMP-JT) in heterogeneous scenario,if joint transmission(JT) users are firstly scheduled,other non-JT users will not be allocated sufficient resources,i.e.,scheduling relevancy exists in the users under different cells in the same coordination cluster.However,the CoMP system throughput will decline remarkably,if the impact of scheduling relevancy is not considered.To address this issue,this paper proposes a novel scheduling scheme for CoMP in heterogeneous scenario.The principles of the proposed scheme include two aspects.Firstly,this scheme gives priority to user fairness,based on an extended proportional fairness(PF) scheduling algorithm.Secondly,the throughput of the coordination cluster should be maintained at a high level.By taking the non-CoMP system as a baseline,the proposed scheme is evaluated by comparing to random PF(RPF) and orthogonal PF(OPF) scheme.System-level simulation results indicate that,the proposed scheme can achieve considerable performance gain in both cell average and cell edge throughput.     

Efficient allocation of LTE downlink spectral resource to improve fairness and throughput

For the current generation of cellular communication systems, long‐term evolution (LTE) has been the major protocol to support high‐speed data transmission. It is critical to allocate downlink spectral resource in LTE, namely, resource blocks (RBs), but the issue is not well addressed in the standard. Therefore, the paper develops an efficient RB allocation algorithm with 4 mechanisms to improve both fairness and throughput in LTE. For fairness concern, our RB allocation algorithm uses a resource‐reservation mechanism to prevent cell‐edge user equipments from starvation, and a credit‐driven mechanism to keep track of the amount of resource given to each user equipment. For throughput concern, it adopts both weight‐assignment and RB‐matching mechanisms to allocate each RB to a packet according to its flow type and length. Through simulations, we demonstrate that the proposed RB allocation algorithm can significantly increase both throughput and fairness while reducing packet dropping and delays of real‐time flows, as compared with previous methods.     

AF中继下行链路系统的能效资源分配方案

为最大化放大转发中继系统的下行链路总能效,结合系统的电路功率,提出了一种基于能效的中继选择和功率分配联合方案.为降低复杂度,采用分步式次优化方案,利用虚拟直传信道增益得到中继选择方法,并将中继系统转换为单跳系统;然后利用凸规划得到最优功率分配.此外,为适应不同的用户分布,提出联合小区呼吸机制的分配方案.仿真结果表明,所提次优联合方案逼近最优值,联合小区呼吸的方案可适应不同的用户分布并进一步提升能效.     

Coalition-based downlink resource allocation for LTE system with divide-and-conquer approach

To take advantage of the multiuser diversity resulted from the variation in channel conditions among the users,it has become an interesting and challenging problem to efficiently allocate the resources such as subcarriers,bits,and power.Most of current research concentrates on solving the resource-allocation problem for all users together in a centralized way,which brings about high computational complexity and makes it impractical for real system.Therefore,a coalitional game framework for downlink multi-user resource allocation in long term evolution(LTE) system is proposed,based on the divide-and-conquer idea.The goal is to maximize the overall system data rate under the constraints of each user’s minimal rate requirement and maximal transmit power of base station while considering the fairness among users.In this framework,a coalitional formation algorithm is proposed to achieve optimal coalition formation and a two-user bargaining algorithm is designed to bargain channel assignment between two users.The total computational complexity is greatly reduced in comparison with conventional methods.The simulation results show that the proposed algorithms acquire a good tradeoff between the overall system throughout and fairness,compared to maximal rate and max-min schemes.     

Joint downlink and uplink resource allocation for multi-carrier SWIPT system

A multi-carrier simultaneous wireless information and power transfer (SWIPT) communication system including one base station (BS) and one user was investigated,where both uplink and downlink adopt orthogonal frequency division multiplexing (OFDM).In the downlink,the BS transmited information and power to the user simultaneously.In the uplink,the user transmited information to the BS by using the power harvested from the BS in the downlink.The weighted sum of the downlink and uplink achievable rates by jointly optimizing subcarrier allocation and power allocation of the uplink and downlink were aimed to maximized.An optimal algorithm to solve the joint resource allocation problem was proposed,which was based on the Lagrange duality method and the ellipsoid method.Finally,the result shows the performances of the proposed algorithm by computer simulations.     

多业务MIMO-OFDMA/SDMA系统跨层调度与动态资源分配

对多业务MIMO-OFDMA/SDMA 系统下行链路跨层调度与动态资源分配问题进行了研究.首先,在满足各种约束条件的前提下,以最大化系统吞吐量为目标建立了相应的优化模型;然后,提出了一种基于业务类型和子空间距离的用户分组算法,该算法采用聚类分析的方法在每个子载波上对配置有多根接收天线的用户进行分组,从而降低了调度时所需搜索的用户空间的维数;接着,基于所提出的用户分组算法并结合不同业务的优先级提出了一种新的跨层调度和资源分配算法,该算法充分利用跨层信息为每个子载波调度相应的用户组,并为调度到的用户分配相应的系统资源,从而通过最大化每个子载波的吞吐量近似实现了系统整体吞吐量的最大化.仿真结果表明,与现有的方案相比,所提算法更好地满足了不同业务用户的QoS要求,并获得了更好的吞吐量性能.     

Relax online resource allocation algorithms for D2D communication

Maximizing the system sumrate by sharing the resource blocks among the cellular user equipments and the D2D (device to device) pairs while maintaining the quality of service is an important research question in a D2D communication underlaying cellular networks. The problem can be optimally solved in offline by using the weighted bipartite matching algorithm. However, in long‐term evolution and beyond (4G and 5G) systems, scheduling algorithms should be very efficient where the optimal algorithm is quite complex to implement. Hence, a low complexity algorithm that returns almost the optimal solution can be an alternative to this research problem. In this paper, we propose 2 less complex stable matching–based relax online algorithms those exhibit very close to the optimal solution. Our proposed algorithms deal with fixed number of cellular user equipments and a variable number of D2D pairs those arrive in the system online. Unlike online matching algorithms, we consider that an assignment can be revoked if it improves the objective function (total system sumrate). However, we want to minimize the number of revocation (ie, the number of changes in the assignments) as a large number of changes can be expensive for the networks too. We consider various offline algorithms proposed for the same research problem as relaxed online algorithms. Through extensive simulations, we find that our proposed algorithms outperform all of the algorithms in terms of the number of changes in assignment between 2 successive allocations while maintaining the total system sumrate very close to the optimal algorithm.     

大规模MIMO OFDMA下行系统能效资源分配算法

针对大规模多输入多输出（MIMO）正交频分多址(OFDMA)下行移动通信系统,提出了一种基于能效最优的资源分配算法。所提算法在采用迫零(ZF)预编码的情况下,以最大化系统能效的下界为准则,同时考虑每个用户的最低速率要求,通过调整带宽分配、功率分配和基站天线数分配来优化能效函数。首先根据优化条件提出了一种迭代算法确定每个用户的带宽分配,然后利用分数规划的性质并采用凸优化方法,通过联合调整基站端的发射天线数和用户的发射功率来优化能效函数。仿真结果表明,所提算法在较少迭代次数的同时能够取得较好的系统能效性能和吞吐量性能。     

Fairness based resource allocation for uplink OFDMA systems

This article investigates two fairness criteria with regard to adaptive resource allocation for uplink orthogonal frequency division multiple access （OFDMA） systems. Nash bargaining solution （NBS） fairness and proportional fairness （PF） are two suitable candidates for fairness consideration, and both can provide attractive trade-offs between total throughput and each user＇s capacity. Utilizing Karush-Kuhn- Tucker （KKT） condition and iterative method, two effective algorithms are designed, to achieve NBS fairness and proportional fairness, respectively. Simulation results show that the proposed resource allocation algorithms achieve good tradeoff between the overall rate and fairness, with little performance loss from the total capacity.     

Robust resource allocation for NOMA-assisted heterogeneous networks

As a promising technology to improve spectrum efficiency and transmission coverage, Heterogeneous Network (HetNet) has attracted the attention of many scholars in recent years. Additionally, with the introduction of the Non-Orthogonal Multiple Access (NOMA) technology, the NOMA-assisted HetNet cannot only improve the system capacity but also allow more users to utilize the same frequency band resource, which makes the NOMA-assisted HetNet a hot topic. However, traditional resource allocation schemes assume that base stations can exactly estimate direct link gains and cross-tier link gains, which is impractical for practical HetNets due to the impact of channel delays and random perturbation. To further improve energy utilization and system robustness, in this paper, we investigate a robust resource allocation problem to maximize the total Energy Efficiency (EE) of Small-Cell Users (SCUs) in NOMA-assisted HetNets under imperfect channel state information. By considering bounded channel uncertainties, the robust resource optimization problem is formulated as a mixed-integer and nonlinear programming problem under the constraints of the cross-tier interference power of macrocell users, the maximum transmit power of small base station, the Resource Block (RB) assignment, and the quality of service requirement of each SCU. The original problem is converted into an equivalent convex optimization problem by using Dinkelbach's method and the successive convex approximation method. A robust Dinkelbach-based iteration algorithm is designed by jointly optimizing the transmit power and the RB allocation. Simulation results verify that the proposed algorithm has better EE and robustness than the existing algorithms.