Energy-Efficient Resource Allocation for Heterogeneous Network with Grouping D2D

In this paper,a new communication model is built named grouping D2D(GD2D).Different from the traditional D2D coordination,we proposed GD2D communication in licensed and unlicensed spectrum simultaneously.We formulate a resource allocation problem,which aims at maximizing the energy efficiency(EE)of the system while guaranteeing the quality-of-service(Qos)of users.To efficiently solve this problem,the non-convex optimization problem is first transformed into a convex optimization problem.By transforming the fractional-form problem into an equivalent subtractive-form problem,an iterative power allocation algorithm is proposed to maximize the system EE.Moreover,the optimal closedform power allocation expressions are derived by the Lagrangian approach.Simulation results show that our algorithm achieves higher EE performance than the traditional D2D communication scheme.     

基于不完美CSI的D2D通信网络鲁棒能效资源分配算法

针对设备到设备(D2D)直连通信网络传统最优资源分配算法在随机信道时延、信道估计误差影响下鲁棒性弱的问题,该文在考虑参数不确定性影响的条件下,提出D2D用户总能效最大的鲁棒资源分配算法.考虑干扰功率门限、用户最小速率需求、最大传输功率和子信道分配约束,建立了下垫式频谱共享模式下多用户D2D网络资源分配模型.基于有界信道不确定性模型,利用最坏准则方法将原非凸鲁棒资源分配问题转换为确定性的凸优化问题.然后利用拉格朗日对偶理论求得资源分配的解析解.仿真结果表明所提出的算法具有很好的鲁棒性.     

基于不完美CSI的D2D通信网络鲁棒能效资源分配算法

针对设备到设备(D2D)直连通信网络传统最优资源分配算法在随机信道时延、信道估计误差影响下鲁棒性弱的问题,该文在考虑参数不确定性影响的条件下,提出D2D用户总能效最大的鲁棒资源分配算法.考虑干扰功率门限、用户最小速率需求、最大传输功率和子信道分配约束,建立了下垫式频谱共享模式下多用户D2D网络资源分配模型.基于有界信道...     

Uplink Resource Sharing and Power Management Scheme for an Underlay D2D Communication

Wireless Personal Communications - With the implementation of device-to-device (D2D) communication in primary cellular networks, there will be notable benefits such as increase in cellular...     

异构网中D2D通信的模式选择和资源分配的研究

将D2D(Device to Device)和家庭小区技术引入蜂窝网络,是未来第五代蜂窝移动通信(5G)的趋势之一.主要研究由宏基站(MBS)和家庭基站(FBS)组成的异构网中的D2D(Device to Device)通信的干扰问题,并提出了一种新颖的模式选择算法和资源分配算法来减少系统间干扰.仿真结果显示,文中提出的算法可以有效减少干扰,提高D2D用户的速率,增加系统吞吐量.     

基于非均衡求解的D2D多复用通信资源块分配算法研究

针对小区内D2D多复用的通信资源块分配问题,该文以一个D2D用户分别复用2个和3个蜂窝为基础,提出基于非均衡求解的D2D多复用模式下的资源块分配方案。利用博弈论将资源块划分问题转化为求解被复用蜂窝用户收益联合最大问题。当纳什均衡解不存在时,分析目标函数特性,在可行域内求解“最优解”,保证对不均衡解处理的最优性;对于均衡解存在的情况,将其取整后作为资源分配方案依据,保持其最优性。通过理论分析及仿真实验表明该算法可以提升系统吞吐率,提高小区通信性能。     

Energy-Efficient Resource Allocation in Wireless Networks

This paper shows that game theory can be used as a unifying framework to study radio resource management in a variety of wireless networks. with different service criteria. It focuses on infrastructure networks where users transmit to a common concentration point such as a base station in a cellular network or an access point. Since most of the terminals in a wireless network are battery-powered, energy efficiency is crucial to prolonging the life of the terminals. Also, in most practical scenarios, distributed algorithms are preferred over centralized ones. Throughout this article it focuses on distributed algorithms with emphasis on energy efficiency. A family of power control games is presented for energy-efficient resource allocation in wireless code-division multiple-access (CDMA) networks and give discussions and conclusions     

D2D通信系统中基于QoS的分簇信道分配算法

D2D(Device-to-Device)通信作为第五代移动通信(5G, 5-generation)的关键技术之一,因其高频谱效率、低能耗等优点受到广泛关注。为了更好地满足D2D用户的服务质量(quality of service, QoS)需求,本文引入用户满意度的概念,提出了一种基于QoS的分簇信道分配算法。该算法运用图论着色方法为D2D用户分配信道,可分为三个步骤:首先构建D2D用户间的干扰图,然后在保证蜂窝用户QoS需求的情况下建立D2D用户的可用颜色列表,最后为D2D用户分簇,位于同一簇内的用户可以共享信道。仿真结果表明,本文算法可以有效提高D2D用户的满意度和系统公平性。      

一种能量有效的多用户OFDM资源分配方案

在无线环境下,随着用户数的增加和速率需求的提高,基站能量消耗越来越大。因此,无线网络中能量有效化的设计变得非常必要。本文研究了一种能量有效的多用户OFDM下行链路的资源分配方案。利用分布式方式,首先根据用户的平均信道增益和最低用户比特要求,结合提出的能量有效准则思想分配子载波数;然后按照各用户分配的子载波数分配信道条件较好的信道;再对每个用户所分配的信道按照最低比特要求平均分配比特数,并利用能量有效准则做最优调整,保证功率最小。仿真结果表明,在满足各用户的误比特率及速率要求的条件下,提出的算法与静态的频分多址资源分配方式相比,功率可减小5～6 dB;同时与已有的一种经典分布式算法相比,功率可减小2～4 dB。     

D2D通信的联合资源分配和功率控制方法

设备到设备(D2D)通信对未来蜂窝网络是一种很有前途的技术,它可以有效地提高系统的吞吐量和延长用户设备的电池寿命。然而,在蜂窝网络中,D2D通信共享频谱会造成干扰。为消除干扰,充分利用D2D通信的优势,提出了一个联合的频谱资源分配和功率控制(RAPC)方法,该方法能够实现总吞吐量最大化,同时保证D2D用户和蜂窝用户所需的最小速率。提出的资源分配和功率控制的优化问题,通过量子粒子群(QPSO)得到近似优化方案的最优解,其中的量子粒子代表资源分配和功率控制的方法,同时制定惩罚函数删除不可行的方法。仿真结果表明,该方法具有更好的性能、系统吞吐量、功率效率和最小速率比其他方法令人满意。     

认知小蜂窝网络中基于干扰温度限制的下行能效资源分配算法

为最大化认知小蜂窝基站的能量效率,本文基于博弈论模型分析了下行联合频谱资源块和功率分配行为.在干扰受限环境下,多个基站采用分布式结构共享空闲频谱资源.为避免累加干扰损害主用户的通信,算法中引入了功率和干扰温度限制.由于具有耦合限制的分数形式的能量效用函数是非凸最优的,通过将其转化为等价的减数形式进行迭代求解.给定频谱资源块分配策略后,主博弈模型可被重新建模为便于求解发射功率的等价子博弈模型,并通过代价的形势解除耦合限制.仿真结果表明,本文所提算法能够收敛到纳什均衡,并有效提高了系统资源利用率和能量效率.     

SWIPT-D2D通信中基于深度强化学习的资源分配

针对信道状态信息未知SWIPT-D2D((Simultaneous Wireless Information and Power Transfer Device to Device)无线通信网络环境下设备间信号干扰以及设备能量损耗问题,提出通过使用近端策略优化(Proximal Policy Optimization, PPO)算法,在满足蜂窝用户通信质量要求的前提下同时对D2D用户的资源块、发射功率以及功率分割比三部分进行联合优化。仿真结果表明,所提算法相比于其他算法能够为D2D用户制定更好的资源分配方案,在保证蜂窝用户保持较高通信速率的同时使D2D用户获得更高的能效。同时,当环境中用户数量增加时,所提算法相比于Dueling Double DQN(Deep Q-Network)以及DQN算法,D2D能效分别平均提高了15.95%和23.59%,当通信网络规模变大时所提算法具有更强的鲁棒性。     

异构云无线接入网场景下D2D通信资源共享与分配

针对异构云无线接入网中的前向链路受限问题,提出了一种基于干扰阈值的设备到设备(Device-to-Device,D2D)多用户分簇方案,并对系统信道和功率资源的分配进行优化。首先根据D2D用户之间的干扰级别,利用着色图理论对多用户进行分簇;然后,在满足D2D用户和蜂窝用户服务质量约束下,建立了基于D2D用户和速率最大化的资源分配模型,并进一步采用二分法对已分簇的D2D用户进行功率优化分配。仿真实验结果验证了所提方案相比传统方案,系统频谱利用率提高了55%以上。     

Resource Allocation Based on Hierarchical Game for D2D Underlaying Communication Cellular Networks

Wireless Personal Communications - The paper studies the device-to-device (D2D) underlaying communication in the case of sufficient spectrum resources available in cellular networks. A hierarchical...     

LTE-A网络中D2D通信的资源分配算法研究

该文研究了D2D通信使用LTE-A网络上行链路的资源分配问题。首先将问题建模为混合整数非线性规划问题(MINLP),其次根据待接入用户对各信道的青睐程度计算特征值列表并形成相应联盟。在保证各用户服务质量(QoS)的情况下,利用最大加权二部图匹配(MWBM)方法为待接入网络用户寻找合适的资源及复用的组合。仿真结果表明,该算法打破了D2D用户在数据传输过程中一直处于专用或者复用模式的束缚,扩大了D2D用户对可选用的资源范围,与现有算法相比,可有效提高系统的总速率。     

Estimation of Distribution Algorithm for Joint Resource Management in D2D Communication

Wireless Personal Communications - Device to device (D2D) communication technique is one of the established means to enhance data rate in next generation wireless systems. Use of same resource of...     

认知网络中D2D全双工通信的速率最大化功率分配算法

针对认知D2D(Device-to-Device)全双工通信网络中,D2D用户共享蜂窝用户上行链路的频谱资源而带来的复杂干扰问题,该文给出了系统传输速率最大化的功率分配方案。该方案首先给出了认知D2D全双工通信模型,并分析了上行链路中基站和D2D用户所受到的干扰以及对应的链路传输速率。其次,提出了一种基于认知无线电系统中最大化D2D用户传输速率的功率分配算法。仿真结果表明,所提算法提高了认知D2D全双工通信网络中上行链路的频谱效率和系统整体传输速率。     

Energy-Efficient Resource Allocation in Mobile Networks with Distributed Antenna Transmission

This paper address the energy conservation issues in wireless downlink of mobile networks with distributed antenna transmission. From the basic information theory for MIMO channels, we derived a simple energy efficiency defined as number of bits per Watt. we then identified three approaches to improve the optimal energy efficiency with a higher capacity, which include alleviating channel fading loss, mitigating the interference, and increasing the number of antennas. We considered the scenario of a single cell with distributed antennas to jointly investigate above three factors. We first proposed a beamforming based energy-efficient resource allocation algorithm, which can achieve the optimal energy efficiency with a higher capacity through adaptively allocating resources and managing interferences. Due to the computational complexity of this algorithm and real-time processing requirement, we further proposed a low-complexity antenna-selection based resource allocation algorithm, which is more tractable and only with slightly performance loss. Finally, we compared different network configurations with these algorithms by extensive simulations, the results demonstrate that the proposed algorithms in distributed antenna configurations achieve better energy efficiency at a high operational throughput point.     

Energy-Efficient Resource Allocation in Multipath CDMA Channels With Band-Limited Waveforms

This paper is focused on the cross-layer design problem of joint multiuser detection and power control for energy-efficiency optimization in wireless data networks through a game-theoretic approach. Unlike previous studies in this area, which have considered the application of game theory to achieve energy-efficiency in idealized synchronous code division multiple access systems, more realistic assumptions including system asynchronism, the use of band-limited chip-pulses, and the multipath distortion induced by the wireless channel are explicitly incorporated in the development of this paper. Several noncooperative games are proposed wherein each user may vary its transmit power and uplink receiver in order to maximize its utility, which is defined here as the ratio of data throughput to transmit power. In particular, the case in which a linear multiuser detector is adopted at the receiver is considered first, and then, the more challenging case in which a nonlinear decision feedback multiuser detector is employed is considered. Via large system analysis (LSA), a decentralized implementation of the power allocation game requiring very little prior information on the interference background is proposed. LSA is also used to compare the energy efficiency of several linear multiuser detectors, and to obtain the optimal (i.e., utility-maximizing) length of the training sequence of each data frame. Numerical results show the effectiveness of the proposed solutions, as well as a very satisfactory agreement of the LSA-based analysis with simulation results obtained for systems with finite (and not so large) numbers of users.      

基于用户窃听的MU-MISO反向散射通信系统鲁棒资源分配算法

针对反向散射通信系统信道估计不准、信息容易被窃听等问题,该文提出一种基于用户窃听的多用户-多输入单输出(MU-MISO)反向散射通信系统鲁棒资源分配算法,以提高系统传输鲁棒性与信息安全性。首先,考虑基站最大功率、时间分配、信道不确定性、能量收集和保密率等约束,建立一个MU-MISO的反向散射通信系统鲁棒资源分配问题。其次,基于非线性能量收集模型和有界球形信道不确定性模型,利用变量松弛法和S过程将原NP-hard问题转化为确定性问题,随后利用连续凸近似、半正定松弛与块坐标下降法将其转化为凸优化问题求解。仿真结果表明,与传统非鲁棒算法对比,所提算法具有较高的系统容量和较低的中断概率。