scholarly journals Codebook-Aided DOA Estimation Algorithms for Massive MIMO System

Electronics ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 26 ◽  
Author(s):  
Shufeng Li ◽  
Hongda Wu ◽  
Libiao Jin
Keyword(s):  
Massive Mimo ◽  
Large Scale ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Computational Cost ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Frame Structure ◽  
Green Communication ◽  
Estimation Algorithms

The conventional direction of arrival (DOA) estimation algorithm is not effective with the tremendous complexity due to the large-scale array antennas in a massive multiple-input multiple-output (MIMO) system. A new frame structure for downlink transmission is presented. Then, codebook-aided (C-aided) algorithms are proposed based on this frame structure that can fully exploit the priori information under channel codebook feedback mechanism. An oriented angle range is scoped through the codebook feedback, which is drastically beneficial to reduce computational burden for DOA estimation in massive MIMO systemss. Compared with traditional DOA estimation algorithms, our proposed C-aided algorithms are computationally efficient and meet the demand of future green communication. Simulations show the estimation effectiveness of C-aided algorithms and advantage for decrement of computational cost.

scholarly journals An Improved Multicell MMSE Channel Estimation in a Massive MIMO System

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ke Li ◽  
Xiaoqin Song ◽  
M. Omair Ahmad ◽  
M. N. S. Swamy
Keyword(s):  
Channel Estimation ◽  
Interference Cancellation ◽  
Massive Mimo ◽  
Large Scale ◽  
Mimo System ◽  
Computational Cost ◽  
Spectrum Efficiency ◽  
Performance Simulation ◽  
Estimation Scheme ◽  
Joint Channel

Massive MIMO is a promising technology to improve both the spectrum efficiency and the energy efficiency. The key problem that impacts the throughput of a massive MIMO system is the pilot contamination due to the nonorthogonality of the pilot sequences in different cells. Conventional channel estimation schemes cannot mitigate this problem effectively, and the computational complexity is increasingly becoming larger in views of the large number of antennas employed in a massive MIMO system. Furthermore, the channel estimation is always carried out with some ideal assumptions such as the complete knowledge of large-scale fading. In this paper, a new channel estimation scheme is proposed by utilizing interference cancellation and joint processing. Highly interfering users in neighboring cells are identified based on the estimation of large-scale fading and then included in the joint channel processing; this achieves a compromise between the effectiveness and efficiency of the channel estimation at a reasonable computational cost, and leads to an improvement in the overall system performance. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

scholarly journals Deep Learning Based Analog Beamforming Design for Millimetre Wave Massive MIMO System

2021 ◽  
Author(s):  
Rajdeep Singh Sohal ◽  
Vinit Grewal ◽  
Jaipreet Kaur ◽  
Maninder Lal Singh
Keyword(s):  
Deep Learning ◽  
Massive Mimo ◽  
Large Scale ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Design Procedure ◽  
Base Station ◽  
Small Scale ◽  
Millimetre Wave ◽  
Input Multiple Output

Abstract Analog beamforming (ABF) architectures for both large-scale antennas at base station (BS) and small-scale antennas at user side in millimetre wave (mmWave) channel are constructed and investigated in this paper with the aid of deep learning (DL) techniques. Transmit and receive beamformers are selected through offline training of ABF network that accepts input as channel. The joint optimization of both beamformers based on DL for maximization of spectral efficiency (SE) for massive multiple input multiple output (M-MIMO) system has been employed. This design procedure is carried out under imperfect channel state information (CSI) conditions and the proposed design of precoders and combiners shows robustness to imperfect CSI. The simulation results verify the superiority in terms of SE of deep neutral network (DNN) enabled beamforming (BF) design of mmWave massive MIMO system compared with the conventional BF algorithms while lessening the computational complexity.

A companding approach for PAPR suppression in OFDM based massive MIMO system

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ajay Kumar Yadav ◽  
Pritam Keshari Sahoo ◽  
Yogendra Kumar Prajapati
Keyword(s):  
Massive Mimo ◽  
Orthogonal Frequency Division Multiplexing ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Average Power ◽  
Base Station ◽  
Convex Optimization Problem ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm

Abstract Orthogonal frequency division multiplexing (OFDM) based massive multiuser (MU) multiple input multiple output (MIMO) system is popularly known as high peak-to-average power ratio (PAPR) issue. The OFDM-based massive MIMO system exhibits large number of antennas at Base Station (BS) due to the use of large number of high-power amplifiers (HPA). High PAPR causes HPAs to work in a nonlinear region, and hardware cost of nonlinear HPAs are very high and also power inefficient. Hence, to tackle this problem, this manuscript suggests a novel scheme based on the joint MU precoding and PAPR minimization (PP) expressed as a convex optimization problem solved by steepest gradient descent (GD) with μ-law companding approach. Therefore, we develop a new scheme mentioned to as MU-PP-GDs with μ-law companding to minimize PAPR by compressing and enlarging of massive MIMO OFDM signals simultaneously. At CCDF = 10−3, the proposed scheme (MU-PP-GDs with μ-law companding for Iterations = 100) minimizes the PAPR to 3.70 dB which is better than that of MU-PP-GDs, (iteration = 100) as shown in simulation results.

scholarly journals The Downlink Performance for Cell-Free Massive MIMO with Instantaneous CSI in Slowly Time-Varying Channels

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1552
Author(s):  
Tongzhou Han ◽  
Danfeng Zhao
Keyword(s):  
Power Control ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Time Varying ◽  
Input Multiple Output ◽  
Efficiency Performance ◽  
A Cell ◽  
Time Varying Channel

In centralized massive multiple-input multiple-output (MIMO) systems, the channel hardening phenomenon can occur, in which the channel behaves as almost fully deterministic as the number of antennas increases. Nevertheless, in a cell-free massive MIMO system, the channel is less deterministic. In this paper, we propose using instantaneous channel state information (CSI) instead of statistical CSI to obtain the power control coefficient in cell-free massive MIMO. Access points (APs) and user equipment (UE) have sufficient time to obtain instantaneous CSI in a slowly time-varying channel environment. We derive the achievable downlink rate under instantaneous CSI for frequency division duplex (FDD) cell-free massive MIMO systems and apply the results to the power control coefficients. For FDD systems, quantized channel coefficients are proposed to reduce feedback overhead. The simulation results show that the spectral efficiency performance when using instantaneous CSI is approximately three times higher than that achieved using statistical CSI.

scholarly journals Research on 5G Millimeter Wave Channel Estimation Algorithm

2019 ◽  
pp. 74-77
Author(s):  
Xu Shuang
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Large Scale ◽  
Low Frequency ◽  
Estimation Algorithm ◽  
Simulation Research ◽  
Wave Technology ◽  
Wave Channel ◽  
Mimo Technology

With the explosive growth in the number of communication users and the huge demand for data from users, Limited low-frequency resources have been far from being satisfied by users. The combination of Massive MIMO technology and millimeter-wave technology has brought new hope to users. In this paper, several basic algorithms are placed under the millimeter wave large-scale antenna channel for simulation research.

Angle-Domain Channel and DOA Estimation in Airborne Massive MIMO System with Eavesdropper

2019 ◽  
Author(s):  
Ming Zhang ◽  
Chengjian Liao ◽  
Kui Xu ◽  
Wei Xie ◽  
Jianhui Xu ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Mimo System ◽  
Doa Estimation

scholarly journals Extended Coprime Array Configuration Generating Large-Scale Antenna Co-Array in Massive MIMO System

2019 ◽  
Vol 68 (8) ◽  
pp. 7841-7853 ◽  
Author(s):  
Wang Zheng ◽  
Xiaofei Zhang ◽  
Yunfei Wang ◽  
Mengjie Zhou ◽  
Qihui Wu
Keyword(s):  
Massive Mimo ◽  
Large Scale ◽  
Mimo System ◽  
Array Configuration ◽  
Coprime Array
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