基于QoS保证的多用户OFDM系统跨层资源分配

针对正交频分复用(OFDM)系统资源分配和调度问题,提出一种基于第三代移动通信长期演进(LTE)系统的分块跨层资源分配算法。此算法考虑物理层的信道状态信息、媒体接入层(MAC)的有限用户缓存队列长度、用户的丢失率和时延等QoS要求,以提高系统频谱效率为总体目标。通过从实时视频业务和混合业务两种业务类型下进行大量对比分析,得出提出的算法能有效提高系统的频谱效率和降低系统时延。     

Dynamic resource allocation in adaptive wireless OFDMA systems

Modern wireless orthogonal frequency division multiple access (OFDMA) systems incorporate dynamic resource allocation (DRA), adaptive modulation and coding (AMC), and power control (PC) to exploit multiuser diversity and achieve higher system throughput. In the literature, only a few proposed algorithms deal with the contiguous DRA problem according to which a contiguous collection of resources can be allocated to each user. This paper formulates this high complexity problem, provides a suitable decision metric and a simple yet efficient solution. The proposed algorithm allocates in each step a contiguous collection of resources to the pending user that leads to the highest estimated correctly received number of bits. Simulation results show that, in this way, considerably improved performance can be achieved in terms of overall system throughput, spectral efficiency, and served traffic. Copyright © 2010 John Wiley & Sons, Ltd.     

OFDMA上行链路中基于博弈论的子载波和功率分配算法

传统OFDMA上行链路资源分配算法中一般以最大化各用户速率或最小化发射功率为依据对子载波和功率进行分配,而对于各用户的功率效率问题并没有加以考虑。针对这一问题,该文提出了一种基于功率效率最优的联合子载波功率分配算法。首先给出了在各用户峰值功率约束条件下达到收益函数最优的必要条件并证明了算法纳什均衡的存在及唯一性,然后给出了子载波功率分配算法。仿真表明:相比最大边界速率子载波和功率分配算法(MaxRt+WF)和固定子载波和功率分配算法(MaxFA+WF),该文算法能大幅度提高各用户的功率效率。同时如果合理地选择代价参数,算法获得的和功率效率能够达到更大。     

基于资源分配和功率控制的D2D中继选择

为优化蜂窝用户通信与设备直传(D2D)中继通信共存下的同频干扰问题,满足蜂窝用户容量要求,提出了一种基于能效的联合资源分配和功率控制的D2 D中继选择算法.该算法首先对等效D2 D中继链路进行资源分配,减小算法复杂度的同时使得D2 D链路对蜂窝链路产生的干扰最小;然后以资源分配结果和功率控制算法为依据进行中继选择.该方案不仅考虑了D2 D中继链路的能效问题,而且还同时考虑到了对蜂窝链路的干扰问题.通过仿真验证,所提算法不仅能有效提升D2 D中继链路的能效值,同时降低了对蜂窝用户的干扰.     

Resource allocation algorithm in LTE uplink SC-FDMA system for time-varying channel with imperfect channel state information

In long term evolution (LTE) uplink single carrier frequency division multiple access (SC-FDMA) system, the restriction that multiple resource blocks (RBs) allocated to a user should be adjacent, makes the resource allocation problem hard to solve. Moreover, with the practical constraint that perfect channel state information (CSI) cannot be obtained in time-varying channel, the resource allocation problem will become more difficult. In this paper, an efficient resource allocation algorithm is proposed in LTE uplink SC-FDMA system with imperfect CSI assumption. Firstly, the resource allocation problem is formulated as a mixed integer programming problem. Then an efficient algorithm based on discrete stochastic optimization is proposed to solve the problem. Finally, simulation results show that the proposed algorithm has desirable system performance.     

OFDM-UWB系统基于用户速率的多用户动态资源分配算法

在原有动态资源分配算法基础上,提出了一种基于用户速率需求的动态资源分配算法。该算法在满足用户数据速率需求和服务质量要求(QoS)的前提下,以用户公平性为原则,分步执行子载波和比特分配来降低系统总的发射功率。首先,通过比较不同子载波对用户速率的影响,引入速率影响因子,对子载波进行分配;然后为每个用户子载波分配比特,并根据用户速率需求进行比特调整。为了进一步降低系统的复杂度,提出了一种通过子载波分组来完成子载波比特分配的方法。仿真结果表明,该算法能够降低系统功耗、误码率和系统复杂度。     

Joint resource allocation for hybrid NOMA-assisted MEC in 6G networks

Multi-access Edge Computing (MEC) is an essential technology for expanding computing power of mobile devices, which can combine the Non-Orthogonal Multiple Access (NOMA) in the power domain to multiplex signals to improve spectral efficiency. We study the integration of the MEC with the NOMA to improve the computation service for the Beyond Fifth-Generation (B5G) and the Sixth-Generation (6G) wireless networks. This paper aims to minimize the energy consumption of a hybrid NOMA-assisted MEC system. In a hybrid NOMA system, a user can offload its task during a time slot shared with another user by the NOMA, and then upload the remaining data during an exclusive time duration served by Orthogonal Multiple Access (OMA). The original energy minimization problem is non-convex. To efficiently solve it, we first assume that the user grouping is given, and focuses on the one group case. Then, a multilevel programming method is proposed to solve the non-convex problem by decomposing it into three subproblems, i.e., power allocation, time slot scheduling, and offloading task assignment, which are solved optimally by carefully studying their convexity and monotonicity. The derived solution is optimal to the original problem by substituting the closed expressions obtained from those decomposed subproblems. Furthermore, we investigate the multi-user case, in which a close-to-optimal algorithm with low-complexity is proposed to form users into different groups with unique time slots. The simulation results verify the superior performance of the proposed scheme compared with some benchmarks, such as OMA and pure NOMA.     

Uplink resource allocation and power control for D2D communications underlaying multi-cell mobile networks

Proximity user equipments (UEs) in mobile networks may be communicated directly without passing their traffic through the base station by using device-to-device (D2D) communications. This can be done using the underlaying approach in which the D2D-UEs (DEs) are allowed to use the same resources allocated for cellular UEs (CEs), which can enhance the spectral efficiency. However, if the resource allocation for DEs is not designed appropriately, it would generate harmful interference on CEs communications. Therefore, this paper addresses a resource allocation and power control problems for D2D communications underlaying multi-cell mobile networks with the consideration of the inter-cell and intra-cell interferences. The problem is formulated to maximise the network performance in terms of achieved throughput while ensuring the quality-of-service (QoS) constraints for CEs and DEs. A two-step algorithm is proposed in which the admission control is performed firstly to determine the set of possible D2D connections and their CE partners that achieve the minimum QoS demands. Then, the optimal power for each permissible DE and its possible partners in different cells are allocated to maximise the network throughput. Simulation results illustrate that the suggested algorithm can remarkably enhance the performance of the network in terms of throughput gain and access rate.     

协作多组多播认知无线网络的资源优化配置

考虑到无线电频谱资源日益紧缺,提出了一种基于组间组内协作传输的多播组新机制,涉及多个多播组并使用同一频谱资源以协作方式传输信息。基于认知无线网络中该机制,研究了系统的资源优化配置,理论分析得出了功率分配方案,进而讨论了系统加权总传输速率的优化,同时考虑了主用户和认知用户之间信号干扰及功率限制对传输速率的影响,最优化用户性能。仿真结果表明,优化方案下多播组传输速率随用户人数的增加而上升,达到最优化用户服务质量;当功率限制时,通过设置加权因子,能够保证主用户拥有良好的通信性能。     

LTE-Advanced中继系统中一种公平的下行资源分配机制

LTE-Advanced(LTE-A)系统引入中继后,带来了如提高频谱效率、拓展网络覆盖等优点,但是也给资源分配带来了更多的挑战。针对LTE-A中继系统的下行资源分配问题,在资源足够使用的情况下,提出一种在eNB和中继功率受限且用户数据速率限制的条件下,以权衡系统吞吐量和用户公平性为目标的资源分配机制。通过仿真验证表明,该算法较好地权衡了系统吞吐量和用户公平性,并且能满足用户速率要求。     

Performance analysis of user fair-based relay adaptive power allocation in physical-layer network coding cooperation

Network Coding (NC) is an effective technology to enhance the cooperative system spectral efficiency. However, since it is network-oriented, the existing performance metric of single-user outage can not comprehensively evaluate its gain and the impact to the entire network, which affect the user fairness. This paper proposes two novel user fair-based adaptive relay power allocation algorithms in single-relay NC cooperative multiple access channels. Firstly, common outage probability is employed as the performance metric, and to minimize it, a specific condition is deduced. On this basis, the instantaneous channel information-based adaptive relay power allocation scheme and the channel statistic information-based one with lower complexity are designed respectively, which make users?? signals superimposed at accurately calculated proportion to maintain fairness. Simulation results show that compared with other existing schemes, the proposed schemes can best maintain user fairness, and effectively improve the common outage performance of the whole system, at the expense of small spectral efficiency.     

多天线系统中的二次注水功率分配

Aiming at the problem of resource allocation in multiuser multi-input multi-output （MIMO） systems, a new power allocation algorithm based on dual waterfilling is proposed. Block diagonalization is adopted to cancel the inter-user interference, and then the complete diagonalization method is employed to derive the spatial sub-channels for each user. The overall power of the system is divided among users based on each user＇s large scale fading; then the power of each user is further allocated to its spatial sub-channels based on the small scale fading. Simulation results show that compared with the existing resource allocation strategies, the proposed algorithm can provide more ergodic capacity for multi-user MIMO systems. When the total transmit power is 100w, it has 15% capacity advantage over the traditional waterfilling method.     

System utility based resource allocation for D2D multicast communication in software-defined cellular networks

Device-to-device (D2D) multicast communication is a useful way to improve the communication efficiency of local services. This study considers a scenario of D2D multicast communication in software defined cellular network and investigates the frequency resource allocation problem. Firstly, we build the system model and formulate the optimization problem. Secondly, a hierarchical scheme to achieve a suboptimal solution is proposed. To select appropriate user equipments (UEs) as potential D2D transmitters (PDTs), a social aware PDT selection method is proposed. Then, a resource allocation algorithm considering users’ priorities is proposed. Furthermore, to study the resource allocation for general system that UEs without priorities, a non-priority considered allocation algorithm is proposed also. Numerical simulation results show that the proposed schemes are effective in improving the system utility and reducing the resource consuming for D2D communications.     

OFDM中继系统中能效优化的资源联合分配算法

在协作正交频分复用系统中,合理的资源分配对于提高系统性能具有重要的意义。针对中继、子载波和功率的联合分配,对最大化系统能效为目标的分配算法进行研究,提出了一个最低容量限制下的最大能效次优化资源联合分配算法(JRAA,joint resource allocation algorithm)。该算法使用冲突图表示系统资源冲突关系,根据冲突图的最大独立集结果进行资源分配。经过仿真验证,该资源分配算法实现了中继一子载波和功率的联合分配,在能效性能方面优于现有的算法。     

基于能量效率的分布式星群下行链路功率分配方法研究

针对多波束卫星通信系统星上资源稀缺和能量利用效率不高的问题,本文提出了分布式星群网络下行链路中兼顾系统功耗和数据速率的功率分配方法,通过合理的资源分配来优化系统的能量效率.首先建立分布式星群功率分配模型,将复杂的分式问题转化为易于求解的减法形式问题,然后基于凸优化理论,提出功耗-数据速率权衡功率分配算法,并讨论了能量效率（energy efficiency）与频谱效率（spectral efficiency）之间的权衡关系.仿真结果验证了提出算法的有效性和EE-SE权衡关系,并分析了电路功耗对系统性能的影响.     

Scheduling and Resource Allocation Strategy for OFDMA Systems Over Time-Varying Channels

A cross-layer scheduling and resource allocation (SRA) strategy for an adaptive modulation and coding (AMC) based orthogonal frequency multiple access (OFDMA) system is proposed. The objective of this paper is to maximize the system throughput as a function of the bit error rate (BER) and the spectral efficiency based on the selected modulation and coding schemes (MCSs). The proposed strategy contains two main algorithms. Firstly, the scheduling algorithm that aims to maximize the average system throughput by arranging the users in distinct queues according to their priorities and selecting the best user of each queue individually in order to guarantee a fair user service amongst different priority levels. Secondly, the resource allocation algorithm that allocates the user, bit and power based on the channel conditions of the scheduling users and the transmission power constraints. The transmitter of the investigated AMC-OFDMA system at the assigned base station (BS) divides the transmitted OFDMA frame into sub-channels and assigns each sub-channel to a scheduled user. In this paper, we compare the performance of the proposed SRA with the conventional first in first out (FIFO) queuing based scheduling and resource allocation strategies used for an AMC-OFDMA system. The simulation results show that the investigated AMC-OFDMA system based on the proposed SRA strategy outperforms the conventional approaches.     

Multi-cell uplink power allocation game for user minimum performance guarantee in OFDMA systems

The multi-cell uplink power allocation problem for orthogonal frequency division multiplexing access (OFDMA) cellular networks is investigated with the uplink transmission power allocation on each co-frequency subchannel being defined as a multi-cell non-cooperative power allocation game (MNPG). The principle of the design oftbe utility function is given and a novel utility function is proposed for MNPG. By using this utility function, the minimum signal to interference plus noise ratio (SINR) requirement of a user can be guaranteed. It can be shown that MNPG will converge to the Nash equilibrium and that this Nash equilibrium is unique. In considering the simulation results, the effect of the algorithm parameters on the system performance is discussed, and the convergence of the MNPG is verified. The performance of MNPG is compared with that of traditional power allocation schemes, the simulation results showing that the proposed algorithm increases the cell-edge user throughput greatly with only a small decrease in cell total throughput; this gives a good tradeoff between the throughput of cell-edge users and the system spectrum efficiency.     

Efficient user pairing algorithm for enhancement of spectral efficiency and interference cancelation in downlink NOMA system

A new subcarrier-user allocation algorithm for the downlink non-orthogonal multiple access system is presented in this paper. The proposed algorithm aims to enhance the spectral efficiency of the system and the successive interference cancelation performance by guaranteeing a high difference in channel-gain between the paired users per subcarrier. To enhance the spectral efficiency, the proposed algorithm provides a higher priority to the subcarrier that has a higher best (maximum) channel gain value rather than that has a lower best channel gain value. Also, it pairs the strong user with the second minimum channel-gain user rather than the minimum channel gain user. Besides, the proposed algorithm divides the subcarriers into two groups according to the standard deviation of the channel gain of each subcarrier. Then, it gives the priority to the group with low standard deviation values during subcarrier-user allocation to guarantee a high difference in channel-gain between the paired users per subcarrier. Later, fractional transmit power allocation is applied to distribute the subcarrier power between the paired users. Simulation results prove that the proposed algorithm improves the spectral efficiency of the system, and guarantees a significantly higher difference in channel-gain between the paired users per subcarrier compared to the conventional algorithms.

     

一种低复杂度的分簇多带超宽带系统动态资源分配算法

提出了一种用于多用户多带超宽带系统的低复杂度动态资源分配方案,该方案在满足所有用户数据速率请求和给定的误比特率前提下,可以最小化总的系统传输功率.分析和实验表明,提出的算法与现有方法相比,性能只有很少的损失,却可以显著降低运算的复杂度.复杂度的降低主要通过把一般性的限制性优化问题转化为线性编程问题,并在求解线性编程问题的过程中寻找更好的初始解.此外,还通过对相邻的副载波进行分簇,亦降低了算法的复杂度,并为系统设计提供了更多的灵活性.最后,还通过实验研究了簇的大小和用户数目对算法和系统的影响.     

使用对偶分解的MU-CoMP-JT联合资源分配

在MU-Co MP-JT(Multi-User Coordinated Multiple-Points Joint Transmission)联合资源分配问题中,传统的迫零预编码矩阵会使得每根天线发送功率互不相同,当Co MP节点发射功率仅满足总功率约束时性能损失不明显,而当Co MP节点分布在不同的地理位置时将受到单节点功率约束,这势必会降低系统功率利用率。为了进一步提升系统吞吐量,基于对偶分解理论提出了一种联合预编码优化的资源分配算法。该算法以最大化用户权重速率为目标,将原优化问题分解成若干个优化的子问题,不同子问题对应不同接收天线数的联合优化问题。当子信道的发送天线数大于接收天线数时,通过多次迭代计算得到预编码矩阵,并且预编码矩阵会随着拉格朗日因子的变化而变化。仿真结果表明所提联合预编码优化的联合资源分配算法能够明显提升系统吞吐量,且提高天线功率利用效率。