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 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 BER and Spectrum Efficiency Analysis of Massive MIMO Systems for IoT Application

2019 ◽  
Vol 8 (4) ◽  
pp. 10587-10591
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Large Scale ◽  
Mimo Systems ◽  
Efficiency Analysis ◽  
Spatial Multiplexing ◽  
Spectrum Efficiency ◽  
Estimation Technique ◽  
Information Request ◽  
Factual Data

The fifth era of portable correspondence frameworks (5G) guarantees uncommon degrees of availability and nature of administration (QoS) to fulfill the unremitting development in the quantity of versatile savvy gadgets and the colossal increment in information request. One of the essential ways 5G organize innovation will be practiced is through arrange densification, to be specific expanding the quantity of radio wires per site and sending littler and littler cells. Gigantic MIMO, where MIMO represents numerous info various yield, is generally expected to be a key empowering agent of 5G. This innovation use a forceful spatial multiplexing, from utilizing countless transmitting/accepting reception apparatuses, to duplicate the limit of a remote channel. Such an appropriated engineering gives extra large scale decent variety, and the co-handling at numerous APs completely smothers the between cell obstruction. Contingent upon moderate/quick channel blurring conditions, a few creators recommended versatile LMS, RLS and NLMS based channel estimators, which either require factual data of the channel or are not proficient enough as far as execution or calculations. So as to conquer the above impacts, the work centers around the QR-RLS based channel estimation technique for Massive MIMO frameworks with various regulation plan.

scholarly journals Distributed Structured Compressive Sensing-Based Time-Frequency Joint Channel Estimation for Massive MIMO-OFDM Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Wenjie Zhang ◽  
Hui Li ◽  
Rong Jin ◽  
Shanlin Wei ◽  
Wei Cheng ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Channel Estimation ◽  
Massive Mimo ◽  
Orthogonal Frequency Division Multiplexing ◽  
Spectrum Efficiency ◽  
Ofdm Systems ◽  
Time Frequency ◽  
Common Support ◽  
Mimo Ofdm ◽  
Joint Channel

In massive multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, accurate channel state information (CSI) is essential to realize system performance gains such as high spectrum and energy efficiency. However, high-dimensional CSI acquisition requires prohibitively high pilot overhead, which leads to a significant reduction in spectrum efficiency and energy efficiency. In this paper, we propose a more efficient time-frequency joint channel estimation scheme for massive MIMO-OFDM systems to resolve those problems. First, partial channel common support (PCCS) is obtained by using time-domain training. Second, utilizing the spatiotemporal common sparse property of the MIMO channels and the obtained PCCS information, we propose the priori-information aided distributed structured sparsity adaptive matching pursuit (PA-DS-SAMP) algorithm to achieve accurate channel estimation in frequency domain. Third, through performance analysis of the proposed algorithm, two signal power reference thresholds are given, which can ensure that the signal can be recovered accurately under power-limited noise and accurately recovered according to probability under Gaussian noise. Finally, pilot design, computational complexity, spectrum efficiency, and energy efficiency are discussed as well. Simulation results show that the proposed method achieves higher channel estimation accuracy while requiring lower pilot sequence overhead compared with other methods.

scholarly journals Channel Sounding for Multi-User Massive MIMO in Distributed Antenna System Environment

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 36 ◽  
Author(s):  
Seoyoung Yu ◽  
Jeong Woo Lee
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Reference Signal ◽  
Estimation Algorithm ◽  
Antenna System ◽  
Distributed Antenna System ◽  
Distributed Antenna ◽  
Estimation Scheme

We propose a generation scheme for a sounding reference signal (SRS) suitable for supporting a large number of users in massive multi-input multi-output (MIMO) system with a distributed antenna system (DAS) environment. The proposed SRS can alleviate the pilot contamination problem which occurs inherently in the multi-user system due to the limited number of orthogonal sequences. The proposed SRS sequence is generated by applying a well-chosen phase rotation to the conventional LTE/LTE-A SRS sequences without requiring an increased amount of resource usage. We also propose using the correlation-aided channel estimation algorithm as a supplemental scheme to obtain more reliable and refined channel estimation. It is shown that the proposed SRS sequence and the supplemental channel estimation scheme improve significantly the channel estimation performance in multi-user massive MIMO systems.

scholarly journals Implicit Pilots for an Efficient Channel Estimation in Simplified Massive MIMO Schemes with Precoding

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Mário Marques da Silva ◽  
Rui Dinis ◽  
João Guerreiro
Keyword(s):  
Channel Estimation ◽  
Interference Cancellation ◽  
Massive Mimo ◽  
Matched Filter ◽  
Multiple Input Multiple Output ◽  
Iterative Receiver ◽  
Single Carrier ◽  
Input Multiple Output ◽  
Estimation Scheme ◽  
Spectral Degradation

This paper proposes a new channel estimation scheme based on implicit pilots, optimized for a simplified massive multiple input, multiple output (MIMO), implemented with precoding, combined with Single-Carrier with Frequency-Domain Equalization (SC-FDE) modulations. We propose an iterative receiver that considers an iterative detection with interference cancellation and channel estimation. The channel estimates are usually obtained with the help of pilot symbols and/or training sequences multiplexed with data symbols. Since the required overheads in massive MIMO schemes can be too high, leading to spectral degradation, the use of superimposed pilots (i.e., pilots added to data) is an efficient alternative. Three different types of preprocessing algorithms are considered in this paper: Zero-Forcing Transmitter (ZFT), Maximum Ratio Transmitter (MRT), and Equal Gain Transmitter (EGT). The main advantage of MRT and EGT is that they do not require matrix inversions. Nevertheless, some level of interference is generated in the decoding process. Such interference is mitigated by employing an optimized iterative receiver. By employing the proposed implicit pilots, the performance of MRT and EGT is very close to the Matched Filter Bound just after a few iterations, even when the number of transmit or receiver antennas is not much higher than the number of data streams.

Sign in / Sign up

Export Citation Format

Share Document