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.

scholarly journals Analytical Performance Evaluation of Massive MIMO Techniques for SC-FDE Modulations

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 533
Author(s):  
Daniel Fernandes ◽  
Francisco Cercas ◽  
Rui Dinis
Keyword(s):  
Mobile Communications ◽  
Massive Mimo ◽  
Matched Filter ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Correlation Factor ◽  
Decision Feedback ◽  
Future Generations ◽  
Ongoing Research ◽  
Single Carrier

In the Fifth Generation of telecommunications networks (5G), it is possible to use massive Multiple Input Multiple Output (MIMO) systems, which require efficient receivers capable of reaching good performance values. MIMO systems can also be extended to massive MIMO (mMIMO) systems, while maintaining their, sometimes exceptional, performance. However, we must be aware that this implies an increase in the receiver complexity. Therefore, the use of mMIMO in 5G and future generations of mobile receivers will only be feasible if they use very efficient algorithms, so as to maintain their excellent performance, while coping with increasing and critical user demands. Having this in mind, this paper presents and compares three types of receivers used in MIMO systems, for further use with mMIMO systems, which use Single-Carrier with Frequency-Domain Equalization (SC-FDE), Iterative Block Decision Feedback Equalization (IB-DFE) and Maximum Ratio Combining (MRC) techniques. This paper presents and compares the theoretical and simulated performance values for these receivers in terms of their Bit Error Rate (BER) and correlation factor. While one of the receivers studied in this paper achieves a BER performance nearly matching the Matched Filter Bound (MFB), the other receivers (IB-DFE and MRC) are more than 1 dB away from MFB. The results obtained in this paper can help the development of ongoing research involving hybrid analog/digital receivers for 5G and future generations of mobile communications.

scholarly journals Channel Estimation Performance Analysis of FBMC/OQAM Systems with Bayesian Approach for 5G-Enabled IoT Applications

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Han Wang ◽  
Wencai Du ◽  
Xianpeng Wang ◽  
Guicai Yu ◽  
Lingwei Xu
Keyword(s):  
Channel Estimation ◽  
Compressive Sensing ◽  
Communication Systems ◽  
Channel Model ◽  
Matching Pursuit ◽  
Multiple Input Multiple Output ◽  
Filter Bank Multicarrier ◽  
Channel Parameter ◽  
Input Multiple Output ◽  
Estimation Scheme

A filter bank multicarrier (FBMC) with offset quadrature amplitude modulation (OQAM) (FBMC/OQAM) is considered to be one of the physical layer technologies in future communication systems, and it is also a wireless transmission technology that supports the applications of Internet of Things (IoT). However, efficient channel parameter estimation is one of the difficulties in realization of highly available FBMC systems. In this paper, the Bayesian compressive sensing (BCS) channel estimation approach for FBMC/OQAM systems is investigated and the performance in a multiple-input multiple-output (MIMO) scenario is also analyzed. An iterative fast Bayesian matching pursuit algorithm is proposed for high channel estimation. Bayesian channel estimation is first presented by exploring the prior statistical information of a sparse channel model. It is indicated that the BCS channel estimation scheme can effectively estimate the channel impulse response. Then, a modified FBMP algorithm is proposed by optimizing the iterative termination conditions. The simulation results indicate that the proposed method provides better mean square error (MSE) and bit error rate (BER) performance than conventional compressive sensing methods.

A New Method for MIMO-OFDM Channel Estimation Based on Discrete Wavelet Transform

2012 ◽  
Vol 182-183 ◽  
pp. 2066-2070
Author(s):  
Hui Shi ◽  
Ren Wang Song ◽  
Gang Fei Wang
Keyword(s):  
Wavelet Transform ◽  
Channel Estimation ◽  
Discrete Wavelet Transform ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Mimo Channel ◽  
Discrete Wavelet ◽  
Input Multiple Output ◽  
Estimation Scheme ◽  
Mimo Ofdm

This paper puts forward a suitable channel estimation scheme for multiple input multiple output and orthogonal frequency division multiplexing system (MIMO-OFDM) based on discrete wavelet transform. According to the least-squares standard (LS), this plan uses pilot to estimate the unit impulse response of MIMO channel firstly, then does wavelet denoising in changing domain, in order to reduce the frequency spectrum leakage and improve the estimation precision. At the same time, this method does not need to know channel information in advance, and can follow up the changes of channel on time with good error rate performance.

scholarly journals A Survey on Massive MIMO Systems in Presence of Channel and Hardware Impairments

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 164 ◽  
Author(s):  
Zahra Mokhtari ◽  
Maryam Sabbaghian ◽  
Rui Dinis
Keyword(s):  
Massive Mimo ◽  
Orthogonal Frequency Division Multiplexing ◽  
Mimo Systems ◽  
Low Cost ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Aging Effects ◽  
Hardware Impairments ◽  
Single Carrier ◽  
Input Multiple Output

Massive multiple input multiple output (MIMO) technology is one of the promising technologies for fifth generation (5G) cellular communications. In this technology, each cell has a base station (BS) with a large number of antennas, allowing the simultaneous use of the same resources (e.g., frequency and/or time slots) by multiple users of a cell. Therefore, massive MIMO systems can bring very high spectral and power efficiencies. However, this technology faces some important issues that need to be addressed. One of these issues is the performance degradation due to hardware impairments, since low-cost RF chains need to be employed. Another issue is the channel estimation and channel aging effects, especially in fast mobility environments. In this paper we will perform a comprehensive study on these two issues considering two of the most promising candidate waveforms for massive MIMO systems: Orthogonal frequency division multiplexing (OFDM) and single-carrier frequency domain processing (SC-FDP). The studies and the results show that hardware impairments and inaccurate channel knowledge can degrade the performance of massive MIMO systems extensively. However, using suitable low complex estimation and compensation techniques and also selecting a suitable waveform can reduce these effects.

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 Massive MIMO-NOMA Networks with Imperfect SIC: Design and Fairness Enhancement

2020 ◽  
Author(s):  
Arthur Sousa de Sena ◽  
Pedro Nardelli
Keyword(s):  
Outage Probability ◽  
Power Allocation ◽  
Interference Cancellation ◽  
Massive Mimo ◽  
Multiple Access ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Optimal Solution ◽  
Input Multiple Output ◽  
The Impact

This paper addresses multi-user multi-cluster massive multiple-input-multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA). Assuming the downlink mode, and taking into consideration the impact of imperfect successive interference cancellation (SIC), an in-depth analytical analysis is carried out, in which closed-form expressions for the outage probability and ergodic rates are derived. Subsequently, the power allocation coefficients of users within each sub-group are optimized to maximize fairness. The considered power optimization is simplified to a convex problem, which makes it possible to obtain the optimal solution via Karush-Kuhn-Tucker (KKT) conditions. Based on the achieved solution, we propose an iterative algorithm to provide fairness also among different sub-groups. Simulation results alongside with insightful discussions are provided to investigate the impact of imperfect SIC and demonstrate the fairness superiority of the proposed dynamic power allocation policies. For example, our results show that if the residual error propagation levels are high, the employment of orthogonal multiple access (OMA) is always preferable than NOMA. It is also shown that the proposed power allocation outperforms conventional massive MIMO-NOMA setups operating with fixed power allocation strategies in terms of outage probability.

scholarly journals An Efficient Estimation of the Number of Optimal Iterations for GS Pre-coding in Downlink Massive MIMO Systems

2020 ◽  
Vol 10 (23) ◽  
pp. 8735
Author(s):  
Jae-Hyun Ro ◽  
Woon-Sang Lee ◽  
Hyun-Sun Hwang ◽  
Duckdong Hwang ◽  
Young-Hwan You ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Signal Transmission ◽  
Multiple Input Multiple Output ◽  
Closed Form Solution ◽  
Neumann Series ◽  
Form Solution ◽  
Efficient Estimation ◽  
Input Multiple Output ◽  
Estimation Scheme

This paper proposes an estimation scheme of the number iterations for optimal Gauss–Seidel (GS) pre-coding in the downlink massive multiple input multiple output (MIMO) systems for the first time. The number of iterations in GS pre-coding is one of the key parameters and should be estimated accurately prior to signal transmission in the downlink systems. For efficient estimation without presentations of the closed-form solution for the GS pre-coding symbols, the proposed estimation scheme uses the relative method which calculates the normalized Euclidean distance (NED) between consecutive GS solutions by using the property of the monotonic decrease function of the GS solutions. Additionally, an efficient initial solution for the GS pre-coding is proposed as a two term Neumann series (NS) based on the stair matrix for improving the accuracy of estimation and accelerating the convergence rate of the GS solution. The evaluated estimation performances verify high accuracy in the downlink massive MIMO systems even in low loading factors. In addition, an additional complexity for estimating the number of the optimal iterations is nearly negligible.

scholarly journals Power-Ordered NOMA with Massive MIMO for 5G Systems

2021 ◽  
Vol 11 (8) ◽  
pp. 3541
Author(s):  
Mário Marques da Silva ◽  
Rui Dinis
Keyword(s):  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Added Value ◽  
Block Transmission ◽  
Single Carrier ◽  
Input Multiple Output ◽  
Massive Number ◽  
Receiver Complexity ◽  
Iot Devices ◽  
Cooperative Power

The aim of this article is to study the conventional and cooperative power-order Non-Orthogonal Multiple Access (NOMA) using the Single Carrier with Frequency Domain Equalization (SC-FDE) block transmission technique, associated with massive Multiple-Input Multiple-Output (MIMO), evidencing its added value in terms of spectral efficiency of such combined scheme. The new services provided by Fifth Generation of Cellular Communications (5G) are supported by new techniques, such as millimeter waves (mm-wave), alongside the conventional centimeter waves and by massive MIMO (m-MIMO) technology. NOMA is expected to be incorporated in future releases of 5G, as it tends to achieve a capacity gain, highly required for the massive number of Internet of things (IoT) devices, namely to support an efficient reuse of limited spectrum. This article shows that the combination of conventional and cooperative NOMA with m-MIMO and SC-FDE, tends to achieve capacity gains, while the performance only suffers a moderate degradation, being an acceptable alternative for future evolutions of 5G. Moreover, it is shown that Cooperative NOMA tends to outperform Conventional NOMA. Moreover, this article shows that the Maximum Ratio Combiner (MRC) receiver is very well fitted to be combined with NOMA and m-MIMO, as it achieves a good performance while reducing the receiver complexity.

scholarly journals Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 301
Author(s):  
Jianhe Du ◽  
Jiaqi Li ◽  
Jing He ◽  
Yalin Guan ◽  
Heyun Lin
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Step Length ◽  
Low Complexity ◽  
Base Station ◽  
Estimation Accuracy ◽  
Input Multiple Output

For multi-user millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the precise acquisition of channel state information (CSI) is a huge challenge. With the increase of the number of antennas at the base station (BS), the traditional channel estimation techniques encounter the problems of pilot training overhead and computational complexity increasing dramatically. In this paper, we develop a step-length optimization-based joint iterative scheme for multi-user mmWave massive MIMO systems to improve channel estimation performance. The proposed estimation algorithm provides the BS with full knowledge of all channel parameters involved in up- and down-links. Compared with existing algorithms, the proposed algorithm has higher channel estimation accuracy with low complexity. Moreover, the proposed scheme performs well even with a small number of training sequences and a large number of users. Simulation results are shown to demonstrate the performance of the proposed channel estimation algorithm.

SUPERIMPOSED TRAINING-BASED CHANNEL ESTIMATION FOR MIMO-MB-OFDM UWB SYSTEMS

2008 ◽  
Vol 17 (05) ◽  
pp. 865-870 ◽  
Author(s):  
QINGHAI YANG ◽  
HUAMIN ZHU ◽  
KYUNG SUP KWAK
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Least Square ◽  
Ultra Wideband ◽  
Superimposed Training ◽  
Square Channel ◽  
Channel Estimate ◽  
Input Multiple Output ◽  
Estimation Scheme

A novel channel estimation scheme based on superimposed training is proposed for multiple-input multiple-output multi-band orthogonal frequency division multiplexing ultra-wideband systems. The optimal training symbols are derived with respect to the least-square channel estimate mean square error. Simulation shows that the proposed scheme benefits much higher effective data throughput over the conventional method.

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