大规模MIMO系统中基于用户分类的动态导频分配

针对大规模MIMO系统导频污染问题,提出一种基于用户分类的动态导频分配策略.根据目标小区用户信号强度的方差设置合理的用户信号强度临界值,将目标小区用户分为中心用户和边缘用户.中心用户采用最大载干比算法分配导频,以最大化中心用户总信道容量.边缘用户采用贪婪算法分配导频,以提高每个边缘用户的信干噪比.仿真结果表明,所提策略在提高边缘用户信干噪比的同时能够有效提高系统的信道容量.     

Pilot decontamination in massive MIMO system combining time-shifted and cell sectorization pilot assignment

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.     

大规模MIMO系统中基于图着色的半动态导频分配

针对大规模MIMO系统中存在的导频污染问题,提出了一种基于图着色的半动态导频分配方案。首先,推导出各个小区可以复用导频的用户与其服务基站的最大距离门限。然后,根据该门限值将系统内各小区的用户分为小区中心用户和小区边缘用户;允许各个小区门限值之内的用户（小区中心用户）复用相同的导频;最后,基于图着色理论协同分配各个小区的小区边缘用户的导频,达到降低导频干扰的目的。仿真结果显示,该方案减少了用户间的导频干扰,有效地提升了整个系统的上行可达和速率。     

大规模MIMO系统中基于谱分离的导频去污染

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。     

基于联合用户分组及天线选择的大规模MIMO波束成形

大规模MIMO系统中,当小区用户数与基站天线数较大时,各用户的信道条件不尽相同,提出一种适用于大规模MIMO下行链路的基于联合用户分组及天线选择的迫零波束成形算法。将用户分成两组,选择信道条件较优的一组用户来接收信号,并为每一个发送数据流选择最优的基站天线组合进行通信,以较小的性能损失,换取大规模MIMO 射频电路的成本与功耗的大幅度降低。仿真结果证明,该算法能够较好地实现系统性能与硬件复杂度的折中。     

大规模MIMO系统中的动态导频分配方案

针对多小区大规模多输入多输出(MIMO)系统中存在的导频污染问题,通过分析MMSE信道估计产生的误差,提出了一种动态导频分配方案.该方案将目标小区与相邻小区相邻的边缘区域内的用户进行动态导频分配,剩余区域内的用户进行随机导频分配来提升系统下行链路的平均可达和速率.仿真结果表明,该方法不仅能显著地提升信道估计的性能,而且还能有效地提高整个系统下行链路的可达和速率.     

Pilot scheduling algorithm based on cell classification-cross entropy for massive MIMO

The massive MIMO system is equipped with a large number of antennas at the base station to serve many users, but it is affected by the inter-cell interference which called pilot contamination. A pilot scheduling scheme was designed to reduce the effect of pilot contamination. Pilot scheduling problem belongs to the arrangement optimization problem, and the algorithm computational complexity of greedy algorithm to search the optimal solution is greatly. In order to reduce the influence of the interference of the community, a new pilot scheduling schemes was proposed by so this article using cell classification and cross entropy(CE) mechanism to reduce the effect of pilot contamination on the system. The simulation results show that the proposed algorithm can not only improve the performance of the system, but also reduce the computational complexity.     

Pilot allocation based on user location information in massive MIMO systems

In order to so1ve the prob1em of pi1ot contamination in massive MIMO systems,a pi1ot a11ocation scheme based on user 1ocation information was proposed.The proposed scheme arranged the users according to the po1ar ang1e of the user 1ocation in the po1ar coordinate system with the base station of the ce11 as the po1e,and assigned the pi1ots sequentia11y.Combining with the characteristics of directiona1 antenna,the scheme can reduce the pi1ot contamination and improve the achievab1e rate of the system by contro11ing the mu1tip1exing distance of the pi1ot to a far range.Simu1ation resu1ts show that the proposed scheme can not on1y reduce the pi1ot po11ution between users,but a1so reduce the performance gap between different users and improve the fairness of the system.     

Interference alignment scheme for massive MIMO system

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.     

Pilot contamination mitigation based on antenna subset transmission for mmWave massive MIMO

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.     

Bat algorithm–based beamforming for mmWave massive MIMO systems

In this paper, an optimized analog beamforming scheme for millimeter‐wave (mmWave) massive MIMO system is presented. This scheme aims to achieve the near‐optimal performance.by searching for the optimized combination of analog precoder and combiner. In order to compensate for the occurrence of attenuation in the magnitude of mmWave signals, the codebook‐dependent analog beamforming in conjunction with precoding at transmitting end and combining signals at the receiving end is utilized. Nonetheless, the existing and traditional beamforming schemes involve a more difficult and complicated search for the optimal combination of analog precoder/combiner matrices from predefined codebooks. To solve this problem, we have referred to a modified bat algorithm to find the optimal combination value. This algorithm will explore the possible pairs of analog precoder/combiner as a way to come up with the best match in order to attain near‐optimal performance. The analysis shows that the optimized beamforming scheme presented in this paper can improve the performance that is very close to the beam steering benchmark that we have considered.     

大规模MIMO系统中动态迁移导频分配

大规模多输入多输出(MIMO)技术是5G的关键技术之一,由导频资源有限引起的导频污染是制约其发展的主要瓶颈之一,为此必须对宝贵的导频资源进行合理地分配以减小导频污染。已有的导频分配方案大多考虑静态导频分配,无法很好地适应用户位置不断变化的移动通信环境。文章针对大规模MIMO系统中用户移动时的导频分配问题,提出了一种动态迁移导频分配方法。该方法在两个相邻时隙间仅针对移动幅度较大的用户进行额外的导频优化,根据分配方案选择一个用户与之进行导频交换,对于其他的用户不改变原分配导频。复杂度分析及仿真结果表明,该算法相较于传统的导频分配方法可以显著地降低计算复杂度,并且与传统的导频分配方法具有相近的频谱效率,具有较高的实用价值。     

大规模MIMO系统中基于能效最大化的资源联合优化算法

针对信道条件未知的多小区大规模多输入多输出（MIMO）系统,提出一种对导频序列长度、导频符号功率以及数据符号功率进行联合优化的资源分配算法。采用最大比合并（MRC）接收,考虑电功率和导频污染的影响,并对最大传输功率进行约束从而建立起以能效（EE）最大化为目标的非凸函数模型。根据分数规划的性质,首先将分数形式转化成减式形式,进而分解成一系列凸函数之差（DC）的问题,最后采用交替优化算法联合调整 3 个变量从而达到能效最大化的目标。仿真结果表明,随着最大符号传输功率的增加,所提方案仍然能保持良好系统能效性能。     

Effects and optimization of pilot sequence length on rate in multiuser massive MIMO FDD system

The effect of pilot sequence length on the asymptotic performance of the ergodic rate was investigated for the multiuser massive multiple-input multiple-output (MIMO) frequency division duplexing (FDD) downlink system.Firstly,the analytical expression of the ergodic rate was derived by using the principle of deterministic equivalence,based on which,it was discovered from the analytical results in two-fold that the normalized pilot sequence length (defined as the pilot sequence length divided by the number of BS antennas) tends to zero yet the rate was guaranteed to grow large without limit as long as the BS antenna number continues to increase,the rate saturates to a certain level if the BS antenna number becomes large with fixed pilot sequence length.Moreover,the pilot sequence length was optimized based on the sum-rate maximization within a finite channel coherence time,and a closed-form solution was deduced under a special correlated channel by means of Lambert W function.Simulation results validate the correctness of the theoretical analysis results and verify the effectiveness of the proposed closed-form solution of the optimal pilot sequence length.     

基于混合精度ADC量化的大规模MIMO系统能效联合优化算法

针对在接收端采用混合精度的数模转换器（analog-to-digitalconverter,ADC）的大规模MIMO系统上行链路,提出一种能效优化算法。在采用最大比合并（maximumratiocombining,MRC）检测算法的基础上,推导得到系统上行链路能效的近似闭式表达式。首先确定高精度ADC的占比率,再以低分辨率ADC的量化精度、用户的发射功率和基站端天线数为优化目标的3个变量进行交替迭代得出最优的能效值;并进一步通过调整高精度ADC的占比率分析其对能效和频效的影响。仿真结果表明,所提算法具有较高的能效值,并且可以通过调整占比率实现能效与频效更好地折中。     

Performance analysis of achievable sum‐rate for downlink massive MIMO systems

Massive multiple‐input and multiple‐output (MIMO) has been recognized as a promising technology in the fifth‐generation wireless networks. Under perfect channel state information, we derive three tractable closed‐form expressions that corresponding to the lower bound, approximation, and upper bound on the achievable rate in a massive MIMO downlink system with maximum‐ratio transmission precoding. Based on the proposed closed‐form expressions, the power efficiency of the system is investigated as the number of transmit antennas increases. Simulation results demonstrate the tightness of our proposed closed‐form expressions for the achievable sum‐rate.     

Joint queue control and user scheduling in MIMO broadcast channel under zero‐forcing multiplexing

This paper studies the problem of queue control and user scheduling in multi‐antenna broadcast (downlink) systems under zero forcing beamforming transmit strategy. In the system, we assume that the data packet arrives randomly to the buffered transmitter. By taking the broadcast channel as a controlled queueing system, we deduce the property of queue control function that maximizes the weighted system throughput while guarantees the delay fairness among users. We also present a low‐complexity user selection algorithm with the consideration of queue state and channel state together. Simulation results show that the joint queue control and user selection policy can achieve considerable fairness and stability among users. Copyright © 2009 John Wiley & Sons, Ltd.     

大规模MIMO系统中低复杂度的稀疏信道估计

针对大规模多输入多输出（MIMO）系统信道估计算法复杂度高的缺陷,结合无线通信信道固有的稀疏性提出了一种低复杂度的稀疏信道估计算法。该算法是在传统的离散傅里叶变换（DFT）信道估计的基础上利用分离算法将信道抽头与噪声空间分离开来,使得信道估计时只需要计算信道抽头的部分,因此算法的计算复杂度被大大降低。仿真结果表明,该算法在保持低复杂度的同时,可获得接近最小均方误差（MMSE）性能。     

Channel modeling and analysis for multipolarized massive MIMO systems

In this paper, we use the multipolarized antennas in massive multiple‐input multiple‐output (MIMO) systems to decline the channel orthogonality and enhance the system performance. We propose 3 multipolarized massive MIMO system schemes according to antenna structures of 3 widely used massive MIMO systems and establish 3‐D geometrical channel models. Simulation results show that the multipolarized massive MIMO systems outperform the unipolarized massive MIMO systems in many situations. The multipolarized antennas would be the best choice for massive MIMO systems if the space efficiency and the miniaturization of equipments are of primary concern.     

Blind adaptive receiver for uplink multiuser massive MIMO systems

Herein, we consider uplink multiuser massive multiple‐input multiple‐output systems when multiple users transmit information symbols to a base station (BS) by applying simple space‐time block coding (STBC). At the BS receiver, two detection filters for each user are used to detect the STBC information symbols. One of these filters is for odd‐indexed symbols and the other for even‐indexed symbols. Using constrained output variance metric minimization, we first derive a special relation between the closed‐form optimal solutions for the two detection filters. Then, using the derived special relation, we propose a new blind adaptive algorithm for implementing the minimum output variance‐based optimal filters. In the proposed adaptive algorithm, filter weight vectors are updated only in the region satisfying the special relation. Through a theoretical analysis of the convergence speed and a computer simulation, we demonstrate that the proposed scheme exhibits faster convergence speed and lower steady‐state bit error rate than the conventional scheme.