scholarly journals Design method of multiuser MIMO system using large scale transmit array with low computational cost based on subarray division

2016 ◽  
Vol 5 (11) ◽  
pp. 407-412 ◽  
Author(s):  
Tetsuki Taniguchi ◽  
Yoshio Karasawa
Keyword(s):  
Large Scale ◽  
Design Method ◽  
Mimo System ◽  
Computational Cost ◽  
Multiuser Mimo ◽  
Low Computational Cost

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.

Designing production-friendly machine learning

2021 ◽  
Vol 14 (13) ◽  
pp. 3420-3420
Author(s):  
Matei Zaharia
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Large Scale ◽  
Question Answering ◽  
Failure Modes ◽  
Computational Cost ◽  
Language Models ◽  
Software Systems ◽  
Resource Cost ◽  
Low Computational Cost

Building production ML applications is difficult because of their resource cost and complex failure modes. I will discuss these challenges from two perspectives: the Stanford DAWN Lab and experience with large-scale commercial ML users at Databricks. I will then present two emerging ideas to help address these challenges. The first is "ML platforms", an emerging class of software systems that standardize the interfaces used in ML applications to make them easier to build and maintain. I will give a few examples, including the open-source MLflow system from Databricks [3]. The second idea is models that are more "production-friendly" by design. As a concrete example, I will discuss retrieval-based NLP models such as Stanford's ColBERT [1, 2] that query documents from an updateable corpus to perform tasks such as question-answering, which gives multiple practical advantages, including low computational cost, high interpretability, and very fast updates to the model's "knowledge". These models are an exciting alternative to large language models such as GPT-3.

scholarly journals Pilot Contamination Mitigation via a Novel Time-Shift Pilot Scheme in Large-Scale Multicell Multiuser MIMO Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Zhangkai Luo ◽  
Huali Wang ◽  
Wanghan Lv
Keyword(s):  
Interference Cancellation ◽  
Large Scale ◽  
Mimo Systems ◽  
Mimo System ◽  
Cell Number ◽  
Time Shift ◽  
Pilot Contamination ◽  
Multiuser Mimo ◽  
Pilot Scheme ◽  
A Cell

We propose a novel time-shift pilot scheme to mitigate the pilot contamination in large-scale multicell multiuser MIMO (LS-MIMO) systems. In the proposed scheme, the length of the uplink training pilot sequence is equal to the cell number; that is to say, the same pilot sequence is used within a cell, while for different cells, pilot sequences are mutually orthogonal. Moreover, users within a cell transmit the same pilot sequence in a time-shift manner during the channel estimation stage and in this way all user terminals’ channel state information can be estimated without contamination. The asymptotic channel orthogonality is studied in the LS-MIMO system, with which the mutual interference among cells caused by data and pilot sequences can be cancelled with the successive interference cancellation (SIC) method. We explore the superiority of the proposed scheme in channel coefficient estimation, uplink data detection, and downlink data transmission steps. Theoretical analysis and simulation results demonstrate that the proposed time-shift pilot design can alleviate the pilot contamination problem and improve the performance of the considered system significantly compared with the popular orthogonal pilots.

scholarly journals Main-Branch Structure Iterative Detection Using Approximate Message Passing for Uplink Large-Scale Multiuser MIMO Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Qifeng Zou ◽  
Xuezhi Tan ◽  
Mei Liu ◽  
Lin Ma
Keyword(s):  
Message Passing ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Large Scale ◽  
Mimo Systems ◽  
Mimo System ◽  
Detection Methods ◽  
Iterative Detection ◽  
Multiuser Mimo ◽  
Approximate Message Passing

The emerging large-scale/massive multi-input multioutput (MIMO) system combined with orthogonal frequency division multiplexing (OFDM) is considered a key technology for its advantage of improving the spectral efficiency. In this paper, we introduce an iterative detection algorithm for uplink large-scale multiuser MIMO-OFDM communication systems. We design a Main-Branch structure iterative turbo detector using the Approximate Message Passing algorithm simplified by linear approximation (AMP-LA) and using the Mean Square Error (MSE) criterion to calculate the correlation coefficients between main detector and branch detector for the given iteration. The complexity of our method is compared with other detection algorithms. The simulation results show that our scheme can achieve better performance than the conventional detection methods and have the acceptable complexity.

scholarly journals Large-scale simulation of biomembranes: bringing realistic kinetics to coarse-grained models

2019 ◽  
Author(s):  
Mohsen Sadeghi ◽  
Frank Noé
Keyword(s):  
Large Scale ◽  
Stochastic Dynamics ◽  
Computational Cost ◽  
Coarse Grained ◽  
Fluctuation Spectrum ◽  
Biologically Relevant ◽  
Membrane Models ◽  
Kinetic Effects ◽  
The Cost ◽  
Low Computational Cost

Biomembranes are two-dimensional assemblies of phospholipids that are only a few nanometres thick, but form micrometer-sized structures vital to cellular function. Explicit modelling of biologically relevant membrane systems is computationally expensive, especially when the large number of solvent particles and slow membrane kinetics are taken into account. While highly coarse-grained solvent-free models are available to study equilibrium behaviour of membranes, their efficiency comes at the cost of sacrificing realistic kinetics, and thereby the ability to predict pathways and mechanisms of membrane processes. Here, we present a framework for integrating coarse-grained membrane models with anisotropic stochastic dynamics and continuum-based hydrodynamics, allowing us to simulate large biomembrane systems with realistic kinetics at low computational cost. This paves the way for whole-cell simulations that still include nanometer/nanosecond spatiotemporal resolutions. As a demonstration, we obtain and verify fluctuation spectrum of a full-sized human red blood cell in a 150-milliseconds-long single trajectory. We show how the kinetic effects of different cytoplasmic viscosities can be studied with such a simulation, with predictions that agree with single-cell experimental observations.

scholarly journals Performance of ZF and CB Precoding Techniques for Large-Scale MU-MIMO System

2019 ◽  
Vol 8 (2) ◽  
pp. 5529-5536
Keyword(s):  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Large Scale ◽  
Mimo System ◽  
New Technology ◽  
Vital Role ◽  
Base Station ◽  
Multiuser Mimo ◽  
Channel State ◽  
User Interference

Large Scale Multi User-MIMO (MU-MIMO) is a key technology with reference to 5G to achieve higher spectrum as well as energy efficiency. The new technology refers to the use of a large number of antennas at the base station serving many user terminals in the same time and frequency resource allowing the channel vectors nearly orthogonal as a result, there is a reduction in inter-user interference and users may be served with the significant data rate. The linear precoding techniques play a vital role in the reduction of interference among users and cells. In this paper, we have derived, analyzed and compared two important precoding techniques i.e. Zero-forcing (ZF) and Conjugate beamforming (CB) for large-scale multiuser-MIMO. We analyze these precoding techniques with respect to spectral efficiency and downlink power with imperfect channel state information (CSI) as well as with perfect CSI. It is shown that ZF performs better as compared to CB precoding for achieving higher spectral efficiency and requires lower downlink power. CB outperforms the ZF in terms of downlink transmit power when there is a requirement to achieve low spectral efficiency and also for celledge users, hence energy efficient in these cases. It is shown from simulation results that ZF precoding is the better choice for attaining higher spectral and energy efficiency for a large scale multiuser-MIMO communication system.

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