scholarly journals Dynamic Beamforming for Three-Dimensional MIMO Technique in LTE-Advanced Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Yan Li ◽  
Xiaodong Ji ◽  
Dong Liang ◽  
Yuan Li
Keyword(s):  
Massive Mimo ◽  
Mimo System ◽  
Three Dimensional ◽  
System Level ◽  
System Level Simulation ◽  
Cell Coverage ◽  
Mimo Networks ◽  
Lte Advanced ◽  
3D Mimo ◽  
Beamforming Algorithm

MIMO system with large number of antennas, referred to as large MIMO or massive MIMO, has drawn increased attention as they enable significant throughput and coverage improvement in LTE-Advanced networks. However, deploying huge number of antennas in both transmitters and receivers was a great challenge in the past few years. Three-dimensional MIMO (3D MIMO) is introduced as a promising technique in massive MIMO networks to enhance the cellular performance by deploying antenna elements in both horizontal and vertical dimensions. Radio propagation of user equipments (UE) is considered only in horizontal domain by applying 2D beamforming. In this paper, a dynamic beamforming algorithm is proposed where vertical domain of antenna is fully considered and beamforming vector can be obtained according to UEs’ horizontal and vertical directions. Compared with the conventional 2D beamforming algorithm, throughput of cell edge UEs and cell center UEs can be improved by the proposed algorithm. System level simulation is performed to evaluate the proposed algorithm. In addition, the impacts of downtilt and intersite distance (ISD) on spectral efficiency and cell coverage are explored.

scholarly journals Resource Allocation for Vertical Sectorization in LTE-Advanced Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Lei Song ◽  
Mugen Peng ◽  
Yan Li
Keyword(s):  
Resource Allocation ◽  
Interference Cancellation ◽  
Multiple Input Multiple Output ◽  
Three Dimensional ◽  
Base Station ◽  
System Level ◽  
System Level Simulation ◽  
Lte Advanced ◽  
Input Multiple Output ◽  
Resource Allocation Scheme

Massive multiple input multiple output (MIMO) technology has been discussed widely in the past few years. Three-dimensional MIMO (3D MIMO) can be seen as a promising technique to realize massive MIMO to enhance the performance of LTE-Advanced systems. Vertical sectorization can be introduced by means of adjusting the downtilt of transmitting antennas. Thus, the radiowave from a base station (BS) to a group of user equipments (UE) can be divided into two beams which point at two different areas within a cell. Intrasector interference is inevitable since the resources are overlapped. In this paper, the influence of intrasector interference is analyzed and an enhanced resource allocation scheme for vertical sectorization is proposed as a method of interference cancellation. Compared with the conventional 2D MIMO scenarios, cell average throughput of the whole system can be improved by vertical sectorization. System level simulation is performed to evaluate the performance of the proposed scheme. In addition, the impacts of downtilt parameters and intersite distance (ISD) on spectral efficiency and cell coverage are presented.

scholarly journals Limited Feedback for 3D Massive MIMO under 3D-UMa and 3D-UMi Scenarios

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Zheng Hu ◽  
Shaoli Kang ◽  
Xin Su
Keyword(s):  
Massive Mimo ◽  
Limited Feedback ◽  
Base Station ◽  
Code Word ◽  
System Level ◽  
Word Index ◽  
Transmission Scheme ◽  
Rectangular Array ◽  
System Level Simulation ◽  
Lte Advanced

For three-dimensional (3D) massive MIMO utilizing the uniform rectangular array (URA) in the base station (BS), we propose a limited feedback transmission scheme in which the channel state information (CSI) feedback operations for horizontal domain and vertical domain are separate. Compared to the traditional feedback scheme, the scheme can reduce the feedback overhead, code word index search complexity, and storage requirement. Also, based on the zenith of departure angle (ZoD) distribution in 3D-Urban Macro Cell (3D-UMa) and 3D-Urban Micro Cell (3D-UMi) scenarios, we propose the angle quantization codebook for vertical domain, while the codebook of long term evolution-advanced (LTE-Advanced) is still adopted in horizontal domain to preserve compatibility with the LTE-Advanced. Based on the angle quantization codebook, the subsampled 3-bit DFT codebook is designed for vertical domain. The system-level simulation results reveal that, to compromise the feedback overhead and system performance, 2-bit codebook for 3D-UMa scenario and 3-bit codebook for 3D-UMi scenario can meet requirements in vertical domain. The feedback period for vertical domain can also be extended appropriately to reduce the feedback overhead.

Massive MIMO System Level Performance Results of a Dense Antenna Array

2021 ◽  
Author(s):  
Zhengxiang Ma ◽  
Leonard Piazzi ◽  
Huairen Yi ◽  
Hady Moussa ◽  
Renjian Zhao
Keyword(s):  
Antenna Array ◽  
Massive Mimo ◽  
Mimo System ◽  
System Level ◽  
Performance Results ◽  
Level Performance

scholarly journals Channel Estimation for Frequency Division Duplexing Multi-user Massive MIMO Systems via Tensor Compressive Sensing

2017 ◽  
Vol 67 (6) ◽  
pp. 668
Author(s):  
Qingzhu Wang ◽  
Mengying Wei ◽  
Yihai Zhu
Keyword(s):  
Channel Estimation ◽  
Compressive Sensing ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Three Dimensional ◽  
Data Representation ◽  
Frequency Division ◽  
Frequency Division Duplexing

<p class="p1">To make full use of space multiplexing gains for the multi-user massive multiple-input multiple-output, accurate channel state information at the transmitter (CSIT) is required. However, the large number of users and antennas make CSIT a higher-order data representation. Tensor-based compressive sensing (TCS) is a promising method that is suitable for high-dimensional data processing; it can reduce training pilot and feedback overhead during channel estimation. In this paper, we consider the channel estimation in frequency division duplexing (FDD) multi-user massive MIMO system. A novel estimation framework for three dimensional CSIT is presented, in which the modes include the number of transmitting antennas, receiving antennas, and users. The TCS technique is employed to complete the reconstruction of three dimensional CSIT. The simulation results are given to demonstrate that the proposed estimation approach outperforms existing algorithms.</p>

scholarly journals Massive MIMO Adaptive Modulation and Coding Using Online Deep Learning

2021 ◽  
Author(s):  
Evgeny Bobrov ◽  
Dmitry Kropotov ◽  
Hao Lu ◽  
Danila Zaev
Keyword(s):  
Deep Learning ◽  
Massive Mimo ◽  
Learning Algorithm ◽  
Adaptive Modulation ◽  
System Level ◽  
Adaptive Modulation And Coding ◽  
Q Learning ◽  
Deep Learning Algorithm ◽  
System Level Simulation ◽  
Fully Connected

The paper describes an online deep learning algorithm for the adaptive modulation and coding in 5G Massive MIMO. The algorithm is based on a fully connected neural network, which is initially trained on the output of the traditional algorithm and then is incrementally retrained by the service feedback of its output. We show the advantage of our solution over the state-of-the-art Q-Learning approach. We provide system-level simulation results to support this conclusion in various scenarios with different channel characteristics and different user speeds. Compared with traditional OLLA our algorithm shows 10% to 20% improvement of user throughput in full buffer case. <br>

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