共查询到19条相似文献,搜索用时 296 毫秒
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研究了单基站功率约束条件下的多点协作多输入单输出干扰下行链路系统的和速率最大化非凸优化问题。为有效求解和速率最大化优化问题,首先采用分层优化方法将和速率最大化优化问题分解成发射功率最小化优化问题和单输入单输出干扰信道的和速率最大化优化问题;其次利用二阶锥规划优化方法求解发射功率最小化优化问题;然后利用凸近似和几何规划方法求解单输入单输出干扰信道的和速率最大化优化问题;最后通过交替求解这两个子优化问题,进而提出了一种新颖的单调协同多点波束成形算法;而且利用单有界序列原理证明了所提算法的收敛性。数值仿真表明所提算法只需约四次迭代即可收敛到稳定点,而且所获得的最优性能非常接近穷举搜索算法的最优性能。 相似文献
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大规模多输入多输出(Massive MIMO)技术通过在基站端配置大规模天线能有效提升5G蜂窝系统容量。考虑信道估计误差对系统性能的影响,该文在多小区大规模MIMO系统中形成了用户信干噪比的非溢出概率约束下最小化系统功率的优化问题。针对非凸概率约束中下行波束难于求解的问题,该文根据矩阵迹的性质将优化问题中的非凸约束缩放,进而提出上下行对偶算法求解波束矢量。为进一步减少多小区系统中信令开销,基于大系统分析,提出了仅采用大尺度信息的分布式算法。仿真结果表明,所提的分布式算法与对偶算法相比,在保证用户信干噪比的概率约束时,降低了大规模MIMO系统中传输瞬时信道状态信息的开销,同时具有良好的鲁棒性。 相似文献
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在现有的卫星多波束联合预编码技术研究中,普遍假设卫星发射机有理想的用户信道信息;遗憾的是,由于长距离信号传播延迟,这种假设并不适合于卫星移动通信系统,特别是地球同步卫星系统.为了解决这个问题,提出了基于部分信道信息的多波束协作传输方法;利用阴影-莱斯信道模型,本文导出了闭合形式的中断容量表示,给出了基于部分信道信息的多波束联合预编码优化算法,克服了现有方法的局限性.仿真结果表明,与传统的单波束频率复用方法比较,提出的方法大大降低了系统的发射功率. 相似文献
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智能反射面(Intelligent Reflecting Surface,IRS)是一种通过重新配置无线传播环境,提高无线通信网络安全性的绿色通信新技术。该文针对IRS辅助的多输入单输出安全通信系统,考虑在合法用户保密率约束下,联合优化基站处的发射波束成形和IRS处无源移相器的反射波束成形,使基站的发射功率最小。为了求解多变量耦合的非凸优化问题,我们提出了拉格朗日函数和粒子群嵌套优化算法,使用粒子群算法搜索IRS的反射波束成形,拉格朗日函数求解对应的发射波束成形,获得非凸优化问题的次优解。论文仿真比较了不同算法下基站所需的发射功率,结果表明所提算法基站所需发射功率更低。 相似文献
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针对信道不确定性影响、用户信息泄露和能效提升等问题,该文提出一种基于不完美信道状态信息的可重构智能反射面(RIS)多输入单输出系统鲁棒资源分配算法。首先,考虑能量收集最小接收功率约束、合法用户最小保密速率约束、基站最大发射功率约束及RIS相移约束,基于有界信道不确定性,建立一个联合优化基站主动波束、能量波束、RIS相移矩阵的多变量耦合非线性资源分配问题。然后,利用Dinkelbach,S-procedure和交替优化方法,将原非凸问题转换成确定性凸优化问题,并提出一种基于连续凸近似的交替优化算法。仿真结果表明,与传统非鲁棒算法对比,所提算法具有较低的中断概率。 相似文献
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本文研究了基于资源效率优化的多小区多用户协同波束成形算法设计。为了权衡系统频谱效率与能源效率,考虑在单基站发射功率约束以及达到用户服务质量需求条件下最大化系统资源效率,即系统能源效率与归一化系统频谱效率的加权和。由于优化变量之间的耦合性以及约束条件的非凸特性,该优化问题是一种非凸优化问题并且难以直接获得最优解。为了求解所考虑的优化问题,本文联合利用凸近似方法和分数规化理论,提出一种多小区下行链路系统中最大化资源效率的交替优化算法。所提算法的收敛性可以由凸近似方法和单调有界理论保证。同时,数值仿真验证了所提算法的有效性。 相似文献
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本文研究了多天线放大转发双向中继系统中在满足源节点信噪比要求条件下最小化系统总功率的波束设计问题。该问题是非凸优化问题,为了有效求解该问题,采用分层优化方法将原问题分解成发送波束成形向量优化、接收波束成形向量优化和中继波束成形矩阵优化三类子问题。发送/接收波束成形向量通过求解Rayleigh商最小化问题来获得。中继波束成形矩阵优化问题通过半正定松弛方法转化成半正定优化问题来求解。在求解这三类优化问题的基础上,提出了一种迭代波束成形算法,并采用单调有界序列定理证明了所提算法的收敛性。计算机仿真表明:所提算法经过若干次迭代即可收敛到稳定点;相比于已有算法,本文算法能显著降低系统总功率。 相似文献
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为了解决恶意干扰攻击、窃听和不完美信道状态信息造成的通信质量降低和安全性差等问题,该文提出一种智能反射面(IRS)辅助的抗干扰安全通信系统鲁棒资源分配算法。首先,基于合法用户的最小安全速率约束、最大发射功率约束和IRS相移约束,在非法节点不完美信道状态信息、干扰器波束成形向量未知的情况下,构建了一个联合优化基站的波束成形向量、人工噪声的协方差矩阵和IRS的相移矩阵的鲁棒资源分配问题。其次,为了求解该非凸问题,利用交替优化、Cauchy-Schwarz不等式、连续凸逼近和泰勒级数展开等方法,将原问题转化为易于求解的凸优化问题。仿真结果表明,与传统算法相比所提算法能有效提高系统安全性、降低功率开销、提高抗干扰裕度,且在一定信道误差范围内能够减低约35%的保密中断概率,具有较强的鲁棒性。 相似文献
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In this paper, an optimal user power allocation scheme is proposed to maximize the energy efficiency for downlink
non-orthogonal multiple access (NOMA) heterogeneous networks (HetNets). Considering channel estimation errors
and inter-user interference under imperfect channel state information (CSI), the energy efficiency optimization
problem is formulated, which is non-deterministic polynomial (NP)-hard and non-convex. To cope with this
intractable problem, the optimization problem is converted into a convex problem and address it by the Lagrangian
dual method. However, it is difficult to obtain closed-form solutions since the variables are coupled with each
other. Therefore, a Lagrangian and sub-gradient based algorithm is proposed. In the inner layer loop, optimal
powers are derived by the sub-gradient method. In the outer layer loop, optimal Lagrangian dual variables are
obtained. Simulation results show that the proposed algorithm can significantly improve energy efficiency compared
with traditional power allocation algorithms. 相似文献
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In this paper,1 we examine the problem of robust power control in a downlink beamforming environment under uncertain channel state information (CSI). We suggest that the method of power control using the lower bounds of signal-to-interference-and-noise ratio (SINR) is too pessimistic and will require significantly higher power in transmission than is necessary in practice. Here, a new robust downlink power control solution based on worst-case performance optimization is developed. Our approach employs the explicit modeling of uncertainties in the downlink channel correlation (DCC) matrices and optimizes the amount of transmission power while guaranteeing the worst-case performance to satisfy the quality of service (QoS) constraints for all users. This optimization problem is non-convex and intractable. In order to arrive at an optimal solution to the problem, we propose an iterative algorithm to find the optimum power allocation and worst-case uncertainty matrices. The iterative algorithm is based on the efficient solving of the worst-case uncertainty matrices once the transmission power is given. This can be done by finding the solutions for two cases: (a) when the uncertainty on the DCC matrices is small, for which a closed-form optimum solution can be obtained and (b) when the uncertainty is substantial, for which the intractable problem is transformed into a convex optimization problem readily solvable by an interior point method. Simulation results show that the proposed robust downlink power control using the approach of worst-case performance optimization converges in a few iterations and reduces the transmission power effectively under imperfect knowledge of the channel condition. 相似文献
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In view of multicell downlink time division multiplexing (TDD) massive multiple-input multiple-output (MIMO) systems which had imperfect channel state information (CSI),the beamforming problem that minimized the total transmit power and signal leakage power based on quality of service (QoS) was studied.First,the objective problem was approximated as a standard convex optimization problem.Then,by using the duality of uplink and downlink,an inner and outer layer iterative algorithm was proposed.Numerical results show that,comparing with other typical downlink multicell massive MIMO beamforming algorithms,the proposed algorithm has obvious advantages in terms of complexity and energy efficiency. 相似文献
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无线携能通信(SWIPT)技术是解决无线网络能量受限问题的有效方法,该文研究一个由基站(BS)和多用户组成的多载波SWIPT系统,其上行和下行链路均采用正交频分复用(OFDM)技术。在下行链路中,基站向用户同时进行信息与能量传输;在上行链路中,用户利用从基站接收的能量向基站回传信息。该文以最大化上下行加权和速率为目标,联合优化上行和下行的子载波分配和功率分配,提出基于拉格朗日对偶法和椭球法的最优联合资源分配算法。计算机仿真结果证实了该算法的有效性。 相似文献
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The robust linear transceiver design for the more general model of multicell MIMO downlink system with imperfect channel state information is discussed in this paper. Our aim is to minimize the total power of the network while the quality of service (QoS) in terms of mean-square error (MSE) for every user should be strictly guaranteed for every channel realization in the uncertain region. Unfortunately, this problem may be infeasible due to the MSE constraints. Therefore, we provide a complete analysis of this problem by dividing the solutions into two phases. In phase I, a novel approach is devised to check the feasibility of this problem by considering one alternative problem which is always feasible. This alternative problem is troublesome due to infinite nonconvex MSE constraints. To handle this, we propose an iterative algorithm that performs optimization alternatively by switching between the precoders and decoders. The two subproblems in the algorithm can be recast as semidefinite programming problems which can be efficiently solved. In phase II, one novel iterative algorithm is proposed to solve the original robust problem. Finally, simulation results show that our proposed algorithms converge rapidly and can provide guaranteed QoS for all users. Moreover, we also show that, the more antennas at the users, the more power savings it can provide. 相似文献
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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. 相似文献
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To improve energy efficiency and robustness of heterogeneous wireless networks with wireless information and power transfer,the robust joint transmit power and power splitting resource allocation problem was studied.Based on mini-max probability machine and Dinkelbach method,the original NP-hard problem was transformed into a solvable convex optimization form,meanwhile a distributed dual resource allocation algorithm was proposed.Additionally,both computational complexity and robust sensitivity were analyzed.Simulation results show that the proposed algorithm can guarantee the quality of service requirements of macro cellular users and femtocell users under channel uncertainties. 相似文献