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针对多蜂窝多用户异构无线网络干扰管理和效率提升问题,该文研究了基于干扰效率最大的下行链路基站(BS)-用户匹配和功率分配问题。首先,考虑宏用户和微蜂窝用户的服务质量,将问题建模为多变量混合整数非线性规划问题。其次将原问题分解为基站选择和功率分配两个子问题。针对基站选择问题,利用凸优化问题获得最优基站选择策略;针对功率分配问题,利用二次变换法和Dinkelbach辅助变量法,将功率分配问题转换为凸优化问题求解。仿真结果表明,与现有算法对比,该算法具有较好的干扰效率和干扰控制性能。 相似文献
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近年来,将无人机应用在无线通信网络中来提高系统性能的研究越来越普遍。针对无人机辅助移动用户通信的下行无线传输系统,提出了一种基于用户轨迹的无人机辅助通信系统无线资源分配和航迹优化方法。根据已知的用户运动轨迹提前获取估计的大尺度信道状态信息,以最大化用户的最小平均速率为目标,建立了一个联合优化无人机通信带宽分配和飞行航迹优化的问题。该问题是一个非凸优化问题,要优化的变量之间存在非线性耦合,通过引入辅助变量和分离变量交替优化的方法,将原问题分解为2个可以求解的近似凸优化子问题,并利用连续凸逼近方法对2个子问题交替迭代优化,得到原非凸问题一个近似次优解。仿真结果表明,所提方法能够有效提高用户的平均数据吞吐量,在保证所有用户的通信质量的前提下提高无人机辅助通信的效率。 相似文献
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针对多信道认知用户能量效率问题,提出认知用户能量效率优化模型,进而优化传输功率和感知帧长。首先,多信道认知用户基于多带宽联合能量检测方案,在一定传输功率和干扰功率限制下,建立了以单位数据能耗为目标的最优化问题;其次,通过非线性分式规划的对偶优化将目标函数转换为内点法求解形式;然后,结合内点法和二分法给出算法流程,进而配置最优功率和感知时间。仿真结果表明,对应不同通信环境采用该优化方法都能通过配置最优功率和感知时间达到能量效率最优。 相似文献
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为了满足网络切片多样化需求,实现无线虚拟资源的动态分配,该文提出在C-RAN架构中基于非正交多址接入的联合用户关联和功率资源分配算法。首先,该算法考虑在不完美信道条件下,以切片和用户最小速率需求及时延QoS要求、系统中断概率、前传容量为约束,建立在C-RAN场景中最大化长时平均网络切片总吞吐量的联合用户关联和功率分配模型。其次,将概率混合优化问题转换为非概率优化问题,并利用Lyapunov优化理论设计一种基于当前时隙的联合用户调度和功率分配的算法。最后采用贪婪算法求得用户关联问题次优解;基于用户关联的策略,将功率分配的问题利用连续凸逼近方法将其转换为凸优化问题并采用拉格朗日对偶分解方法获得功率分配策略。仿真结果表明,该算法能满足各网络切片和用户需求的同时有效提升系统时间平均切片总吞吐量。 相似文献
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针对蜂窝网络传输性能及基站(BS)缓存能力受限,多用户内容请求难以满足用户服务质量(QoS)需求等问题,该文提出一种蜂窝终端直通(D2D)通信联合用户关联及内容部署算法。考虑到位于特定区域的多用户可能对于相同内容存在内容请求,该文引入成簇思想,提出一种成簇及内容部署机制,通过为各簇头推送热点内容,而簇成员基于D2D通信模式关联簇头获取所需内容,可实现高效内容获取。综合考虑成簇数量、用户关联簇头、簇头缓存容量及传输速率等限制条件,建立基于用户总业务时延最小化的联合成簇及内容部署优化模型。该优化问题是一个非凸的混合整数优化问题,该文运用拉格朗日部分松弛法,将原优化问题等价转换为3个凸优化的子问题,并基于迭代算法及Kuhn-Munkres算法联合求解各子问题,从而得到联合成簇及内容部署优化策略。最后通过MATLAB仿真验证所提算法的有效性。 相似文献
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针对一对主用户和M对次用户构成的认知无线电网络(cognitive radio network,CRN),研究了非线性能量收集的认知无线电网络的次用户吞吐量最大化问题。具体来说,对于考虑次用户发射器(secondary transmitter,ST)电路功率的情况,首先将主用户吞吐量需求下的次用户吞吐量最大化(secondarythroughput maximization,STM)问题建模为一个非线性优化问题,然后将它转化成凸优化问题,最后提出一种联合使用黄金分割和二分法的低复杂度算法,获得主用户发射器(primarytransmitter,PT)能量传输和次用户信息传输的最优时间分配以及主用户发射器的最优发射功率。对于忽略次用户发射器电路功率的情况,首先证明次用户吞吐量最大化问题的凸特性,然后设计了一个更高效的算法来求解。仿真结果表明,相比等时间分配方案和链路增益优先级方案,提出的设计算法能显著提升次用户吞吐量。 相似文献
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In order to address the unfair user-centric energy efficiency (EE) problem caused by channel difference in the backscatter-assisted wireless powered communication network,a resource allocation scheme was proposed.Firstly,a mixed integer nonconvex fractional programming problem was formulated to maximize the minimum user-centric EE,subject to the quality of service and energy-causality constraints.Based on the generalized fractional programming theory,the original problem was transformed into a mixed integer nonconvex subtraction problem.With the aid of the slack variable,the proof by contradiction,the auxiliary variable and the mixed integer nonconvex subtraction problem were further transformed into an equivalent convex problem.Finally,an iterative algorithm was proposed to obtain the optimal solutions.Computer simulations validated the quick convergence of the proposed iterative algorithm,and that the developed resource allocation scheme efficiently guarantees the fairness among users in terms of EE. 相似文献
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Underlaying device-to-device (D2D) communication is suggested as a promising technology for the next generation cellular networks (5G), where users in close proximity can transmit directly to one another bypassing the base station. However, when D2D communications underlay cellular networks, the potential gain from resource sharing is highly determined by how the interference is managed. In order to mitigate the resource reuse interference between D2D user equipment and cellular user equipment in a multi-cell environment, we propose a resource allocation scheme and dynamic power control for D2D communication underlaying uplink cellular network. Specifically, by introducing the fractional frequency reuse (FFR) principle into the multi-cell architecture, we divide the cellular network into inner region and outer region. Combined with resource partition method, we then formulate the optimization problem so as to maximize the total throughput. However, due to the coupled relationship between resource allocation and power control scheme, the optimization problem is NP-hard and combinational. In order to minimize the interference caused by D2D spectrum reuse, we solve the overall throughput optimization problem by dividing the original problem into two sub-problems. We first propose a heuristic resource pairing algorithm based on overall interference minimization. Then with reference to uplink fractional power control (FPC), a dynamic power control method is proposed. By introducing the interference constraint, we use a lower bound of throughput as a cost function and solve the optimal power allocation problem based on dual Lagrangian decomposition method. Simulation results demonstrate that the proposed algorithm achieves efficient performance compared with existing methods. 相似文献
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Energy‐Efficient Power Allocation for Cognitive Radio Networks with Joint Overlay and Underlay Spectrum Access Mechanism
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Traditional designs of cognitive radio (CR) focus on maximizing system throughput. In this paper, we study the joint overlay and underlay power allocation problem for orthogonal frequency‐division multiple access–based CR. Instead of maximizing system throughput, we aim to maximize system energy efficiency (EE), measured by a “bit per Joule” metric, while maintaining the minimal rate requirement of a given CR system, under the total power constraint of a secondary user and interference constraints of primary users. The formulated energy‐efficient power allocation (EEPA) problem is nonconvex; to make it solvable, we first transform the original problem into a convex optimization problem via fractional programming, and then the Lagrange dual decomposition method is used to solve the equivalent convex optimization problem. Finally, an optimal EEPA allocation scheme is proposed. Numerical results show that the proposed method can achieve better EE performance. 相似文献
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Aiming at the scenarios which consider the constraint of backhaul capacity restriction and interference threshold in ultra-dense networks (UDN),an integer linear programming (ILP) and Lagrangian dual decomposition (LDD) based joint optimization algorithm of energy efficiency and spectrum efficiency was proposed.In the proposed algorithms,the user association problem with the constraint of limited backhaul capacity was modelled as an ILP problem and then finished the connection between the user and the base station of microcell by solving this problem with dynamic programming method.Therefor,Lagrangian dual decomposition (LDD) was applied in an iteration algorithm for spectrum resource allocation and power allocation.The simulation results show that compared with traditional schemes,the proposed algorithm can significantly improve the energy efficiency and spectrum efficiency of system and use the microcell’s load capacity more efficiently. 相似文献
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A joint resource optimization and adaptive modulation framework for uplink single‐carrier frequency‐division multiple access systems
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In this paper, we study joint resource allocation and adaptive modulation in single‐carrier frequency‐division multiple access systems, which is adopted as the multiple access scheme for the uplink in the 3GPP Long Term Evolution standard. We formulate an adaptive modulation and sum‐cost minimization (JAMSCmin) problem. Unlike orthogonal frequency‐division multiple access, in addition to the restriction of allocating a subchannel to one user at most, the multiple subchannels allocated to a user in single‐carrier frequency‐division multiple access systems should be consecutive as well. This renders the resource allocation problem prohibitively difficult and the standard optimization tools (e.g., Lagrange dual approach widely used for orthogonal frequency‐division multiple access, etc.) cannot help towards its optimal solution. We propose a novel optimization framework for the solution of this problem that is inspired from the recently developed canonical duality theory. We first formulate the optimization problem as binary‐integer programming (BIP) problem and then transform this BIP problem into continuous space canonical dual problem that is the concave maximization problem. Based on the solution of the canonical dual problem, we derive joint resource allocation and adaptive modulation algorithm, which has polynomial time complexity. We provide conditions under which the proposed algorithm is optimal. We compare the proposed algorithm with the existing algorithms in the literature. The results show a tremendous performance gain. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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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。 相似文献
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本文研究具有直接通信链路的OFDM解码转发(Decode-and-Forward,DF)中继系统的子载波配对与功率分配算法,目标是在满足业务时延QoS要求的前提下最大化系统容量.利用有效容量模型,首先把OFDM DF中继系统的子载波配对与功率分配问题形成为混合整数规划问题,然后把其转化为连续松弛凸规划问题,利用凸优化方法得到原问题的最优解,从而提出了一种联合最优的子载波配对与功率分配迭代算法.理论推导结果和仿真结果表明,最优子载波配对与功率分配不仅取决于子载波的信道增益,还取决于业务的时延QoS要求.与已有算法相比,本文算法获得的有效容量最大. 相似文献