共查询到20条相似文献，搜索用时 31 毫秒
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Pilot contamination is appeared in massive MIMO (multiple input multiple output) system when using the same pilot sequences at different cells to get the channel state information.It becomes a bottleneck problem of massive MIMO when the number of antenna goes infinite.In order to dealt with pilot contamination,a new TS-CSPA joint scheme was proposed.This scheme can mitigate pilot contamination by reduce the reuse of pilot sequence through the time domain and space domain.And the closed-form expression for the achieved rates and signal to interference plus noise ratio(SINR) to verify the advantages of the proposed scheme were given.Numerical results show that significant performance gains to mitigate pilot contamination problem compared to other methods. 相似文献
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Yao ZHANG;Haotong CAO;Meng ZHOU;Long LI;Longxiang YANG 《电子学报:英文版》2020,29(1):190-198
A downlink cell-free massive Multipleinput multiple-output (mMIMO) system is explored. To investigate the impact of hardware distortion on downlink cell-free mMIMO,this paper recalls a well-established model of hardware impairment and derives a new closedform downlink per-user Spectral efficiency (SE) expression for distributed conjugate beamforming precoding. Based on this trackable expression,two power control algorithms,namely max-total-SE and mixed Quality-of-service (QoS) algorithms,are proposed. Numerical results indicate that the downlink per-user SE is primarily limited by the hardware quality of the receiver,especially when the user corresponds to the receiver. In addition,the proposed max-total-SE algorithm has a fast convergence rate and can significantly improve the total SE compared to the Equal power control (EPC) scheme. What's more,our mixed QoS algorithm also performs well in many respects. 相似文献
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该文针对大规模MIMO FDD下行系统,联合考虑信道估计与数据传输两个阶段的资源分配问题,提出一种能效资源分配算法。该方法以最大化能效为目标,以导频时长、导频功率和数据功率为参量,在指定发射功率和频谱效率约束的条件下建立优化模型。由于目标函数无精确解析形式,借助确定性等价原理对其近似并求得闭合表达式。进而,利用分数规划将原分式形式目标函数等价转换为减式形式,再利用目标函数的下界将非凸优化问题逐步释放为相对容易求解的等效问题,最终获得一种3层迭代能效资源优化算法。仿真结果验证了所提算法的有效性,且具有较快的收敛速度。 相似文献
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《Digital Communications & Networks》2021,7(3):362-372
Massive Multiple-Input-Multiple-Output (MIMO) is a promising technology to meet the demand for the connection of massive devices and high data capacity for mobile networks in the next generation communication system. However, due to the massive connectivity of mobile devices, the pilot contamination problem will severely degrade the communication quality and spectrum efficiency of the massive MIMO system. We propose a deep Monte Carlo Tree Search (MCTS)-based intelligent Pilot-power Allocation Scheme (iPAS) to address this issue. The core of iPAS is a multi-task deep reinforcement learning algorithm that can automatically learn the radio environment and make decisions on the pilot sequence and power allocation to maximize the spectrum efficiency with self-play training. To accelerate the searching convergence, we introduce a Deep Neural Network (DNN) to predict the pilot sequence and power allocation actions. The DNN is trained in a self-supervised learning manner, where the training data is generated from the searching process of the MCTS algorithm. Numerical results show that our proposed iPAS achieves a better Cumulative Distribution Function (CDF) of the ergodic spectral efficiency compared with the previous suboptimal algorithms. 相似文献
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无小区大规模MIMO（Cell-Free Massive MIMO,CF-mMIMO）系统中大量的无线接入点在同一时间频率资源中服务所有的用户,具有较高的网络覆盖率和频谱效率,是下一代无线通信的前沿技术之一。然而,正交导频数量的限制以及用户信道质量的差异造成了较严重的用户间干扰。为了优化这一干扰问题,本文提出了无小区大规模MIMO系统中基于图着色的导频分配与功率控制算法。利用基于图着色的导频分配算法降低导频污染,提高了信道估计精度。在此基础上,通过最大-最小功率控制算法降低多用户同频干扰,满足了系统中用户的混合服务质量需求。数值仿真结果表明：所提出的基于图着色的导频分配与功率控制算法可以显著提高系统的95%用户频谱效率以及最小用户速率,较好抑制了CF-mMIMO系统中的用户间干扰。 相似文献
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The performance of massive multiple-input multiple-output （MIMO） system is limited by pilot contamination. To reduce the pilot contamination, uplink and downlink precoding algorithms are put forward based on interference alignment criterion. In the uplink receiving processing, the target function aligns the pilot contamination and the interference signals to the same null space and acquires the maximal space degree of the desired signals. The uplink receiving precoding matrix is solved on maximal signal to interference plus noise ratio （SINR） criterion considering the impact of the pilot contamination on channel estimations. The uplink receiving precoding matrix is used as the downlink transmitting precoding matrix. Exploiting the channel reciprocity, it is proved that, if the uplink receiving precoding matrix achieves maximal S1NR, the identical precoding matrix can be used in the downlink transmission and acquires maximal signal to leakage plus noise ratio （SLNR）. Simulations show that the spectrum efficiency of the proposed algorithm can reach about 1.5 times higher than that of popular matched filtering （MF） precoding algorithm, and about 1.1 times higher than multi-cell minimum mean square error （MMSE） precoding algorithm. The performance of the proposed algorithm can be improved approximately linearly with the increasing of the number of antennas. 相似文献
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导频序列在不同小区中不可避免地被复用,从而产生了导频污染,导频污染带来的干扰不会随着基站天线数的增加而减少。导频污染已成为限制大规模多输入多输出（MIMO）系统性能的主要原因之一,为了减少导频污染带来的影响,文章提出了时移联合空间划分的导频分配方案,该方案通过从时间域和空间域两个方面来减少导频序列的复用次数,从而减少导频污染。推导出了采用该方案时系统中目标上行用户的可达和速率和信干噪比（SINR）。仿真结果表明,所提方案能有效减少导频污染,获得较好的系统性能,提高系统吞吐量。 相似文献
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导频污染问题是限制大规模多输入多输出(MIMO)系统性能的主要影响因素.针对这个问题,提出了一种基于改进预编码和最优导频分配策略的大规模MIMO系统导频污染抑制算法.首先,在系统下通过基于改进遗传优化算法的最大化信干噪比(SINR)预编码算法,获得最优预编码矩阵;然后,通过基于用户信道条件优劣的最优导频分配策略对每个小区用户进行导频分配,从而实现大规模MIMO系统导频污染抑制.通过Matlab仿真结果可知,相对于传统的SINR预编码算法,所提算法的复杂度降低了65%左右,而导频污染抑制性能提升了30%左右.该算法能够有效抑制导频污染,提升大规模MIMO系统的性能. 相似文献
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In this paper, we discuss four different optimization problems for distributed antenna systems (DAS) with and without D2D communication, respectively. The first and the third problems are maximizing spectral efficiency (SE) and energy efficiency (EE) of the DAS with D2D communication on the conditions of the minimum SE of DAS as well as D2D pair, the maximum transmit power of each remote access unit (RAU) and maximum transmit power of D2D transmitter. The second and the forth problems are maximizing SE of the DAS on the conditions of the minimum SE as well as the maximum transmit power of RAUs. We exploit the sub-gradient iteration method to obtain the optimal power allocation and summarize optimal power allocation algorithms for the first and second problems. We exploit fractional programming method to investigate the third and fourth problems and develop corresponding optimal power allocation algorithms. Simulation results demonstrate the effectiveness of the proposed power allocation algorithms and show the SE and EE of the DAS by using D2D communication are much better than DAS without D2D communication. 相似文献
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This paper introduces a sparsity controlled multiple random access scheme for efficient user scheduling in Device-to-Device (D2D) underlaid massive MIMO systems. In order to both avoid collision and enhance the Energy Efficiency (EE) of two-tier Heterogeneous Cellular Networks (HCNs), a unified Compressed Sensing (CS) based interference management strategy is proposed which guarantees concurrent cellular and D2D multi-user transmissions without collision. Specifically, supposing the natural sparsity in practical fifth generation (5G) scenarios and employing the sparse signal processing techniques, an analytical random access based model is adopted where provides several user scheduling and channel gain constraints to permit user identification, channel estimation and data decoding simultaneously. Furthermore, by developing a tractable tradeoff between the total power consumption and overall throughput of D2D tier, the transmission power is optimized such that the EE of D2D tier is maximized. Numerical simulations demonstrate the effectiveness of suggested approach to improve the collision avoidance capability and EE of D2D underlaid massive MIMO systems, even for crowded scenarios where the sparsity constraint does not meet sufficiently. 相似文献
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为解决毫米波大规模多输入多输出(MIMO)系统因功率泄漏导致的能量损耗问题,该文提出基于最小相位误差的波束旋转(MPE-BR)预编码方案。首先,采用基于相移器的波束选择网络,构建波束选择集合,系统中每个射频(RF)链通过选择多个波束达到收集泄漏功率的目的。然后,以最大增益波束为基准,根据最小相位误差准则确定波束选择集合的相位,将所选波束的信道增益近似对准同一方向,使得用户的接收信噪比(SNR)最大,从而提高系统性能。此外,该文对所提预编码算法进行了理论分析,推导了频谱效率上界和能量效率上界。实验验证了理论推导的正确性,仿真结果表明,所提方法具有接近无漏功率的和速率性能,与现有的算法相比,所提方案具有较好的频谱效率和能量效率性能。 相似文献
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为使能量效率最大化,采用随机几何方法对多小区多用户MIMO蜂窝网络的上行链路进行建模,改进系统功耗模型,得到一个关于基站密度、发送信号功率、基站天线数、小区用户数以及导频复用因子的能量效率最大化问题.求解该问题,可得到最优的网络部署方案以及各最优参数与硬件特性、传播环境之间的关系.仿真与数值计算结果显示,超密集网络部署可以显著提高能量效率,但是随着基站密度的进一步增加,能量效率的提升很快饱和.更有趣的是,能量效率最优化所确定的部署方案恰为大规模MIMO情形. 相似文献
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为了克服大规模MIMO的技术瓶颈——上行链路导频污染,与现有盲导频去污染中系统参数同时设计的方法不同,提出了系统参数的分层设计方法,指出不同的系统参数对最终接收信号样本协方差矩阵谱精确分离的作用是不同的,即具有不同的优先级。然后,发现要实现谱分离,期望信号的功率并不一定要高于干扰功率,两者之间的差异才是决定因素。更进一步地,在导频序列长度小于基站接收天线数这种更实际的场景下,首次给出了一种数值算法同样能实现上述的精确谱分离。实验仿真证明,由于分层的参数设计保证了渐近谱的精确分离,所提方案比现有的盲导频去污染方案更适合实际应用。 相似文献
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吴灿;黄俊伟;张书畅 《光通信研究》2018,(1):70-73
由于存在导频污染问题,基站侧高效、高精度地获取信道状态信息对实现大规模多输入多输出（MIMO）正交频分复用系统的潜在优点至关重要。通过使用压缩感知技术,可以有效解决导频污染问题。然而,在压缩感知信道估计算法中,很难直接获取信道稀疏度的先验知识。为了解决这个问题,文章提出一种基于贝叶斯压缩感知的信道估计方法,该方法将稀疏信号的统计信息作为先验知识,并运用于多用户大规模MIMO系统的上行链路。仿真结果表明,与传统的信道估计方法相比,所提方法能有效重构原始信道系数。 相似文献
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Nessrine Smaili Mustapha Djeddou Arab Azrar 《International Journal of Communication Systems》2018,31(14)
This paper tackles the problem of pilot contamination (PC) in mmWave Massive MIMO cellular systems. We propose an analog precoder based on antenna subset transmission technique to mitigate the PC. This technique ensures the interfering signal to become noise‐like signal thus helping a more efficient estimation of channel coefficients. Also, this strategy is low cost and introduces no complexity load. The result shows the effectiveness of the proposed precoder to mitigate PC issue. 相似文献
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In this paper, we consider user centric virtual cells model in distributed antenna systems (DAS). We investigate different power allocation optimization problems with interferences in DAS with and without user centric virtual cells model, respectively. The first objective problem is maximizing spectral efficiency (SE) of the DAS with user centric virtual cells model under the constraints of the minimum SE requirements of each user equipment (UE), maximum transmit power of each remote access unit (RAU). We firstly transform this non-convex objective function into a difference of convex functions (D.C.) problem, and then we obtain the optimal solutions by using the concave-convex procedure (CCCP) algorithm. The second objective problem is maximizing energy efficiency (EE) of the DAS with user centric virtual cells model under the same constraints as the first objective problem. Firstly, we exploit fractional programming theory to obtain the equivalent objective function of the second problem with subtract form, and then transform it into a D.C. problem and use CCCP algorithm to obtain the optimal power allocation. In each part, we propose the corresponding optimal power allocation algorithm and also use similar method to obtain optimal solutions of the same optimization problems in DAS without using user centric virtual cells model. Simulation results are provided to demonstrate the effectiveness of the DAS with user centric virtual cells model, which can significantly improve the SE and the EE of the communication systems. 相似文献
