scholarly journals Channel Estimation Approach with Low Pilot Overhead in FBMC/OQAM Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jun Sun ◽  
Xiaomin Mu ◽  
Dejin Kong ◽  
Qian Wang ◽  
Xinmin Li ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Filter Bank ◽  
Multiple Input Multiple Output ◽  
Performance Loss ◽  
Filter Bank Multicarrier ◽  
Error Ratio ◽  
Multiple Input ◽  
Bit Error Ratio ◽  
Input Multiple Output ◽  
The Cost

In filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems, a large pilot overhead is required due to the existence of the imaginary interference. In this paper, we present an approach to reduce the pilot overhead of channel estimation. A part of pilot overhead is used for transmitting data, and compensating symbols are required and designed to remove the imaginary interference. It is worthwhile to point out that the power of compensating symbols can be helpful for data recovery; hence, the proposed approach decreases the overhead of pilots significantly without the cost of additional pilot energy. In addition, the proposed scheme is extended into multiple input multiple output systems without the performance loss. Compared with the conventional preamble consisting of 3 columns symbols, the pilot overhead is equivalent to 2 column symbols in the proposed preamble. To verify the proposed preamble, numerical simulations are carried out with respects to bit error ratio.

Joint Channel Estimation and Data Detection for STBC MIMO-OFDM Wireless Communication System

2015 ◽  
Vol 24 (04) ◽  
pp. 1550059 ◽  
Author(s):  
Gajanan R. Patil ◽  
Vishwanath K. Kokate
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Data Detection ◽  
Channel Estimate ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm ◽  
The Cost ◽  
Joint Channel

This paper presents a joint channel estimation and data detection technique for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Initial estimate of the channel is obtained using semi-blind channel estimation (SBCE). The whitening rotation (WR)-based orthogonal pilot maximum likelihood (OPML) method is used to obtain the channel estimate. The estimate is further enhanced by extracting information through the received data symbols. The performance of the proposed estimator is studied under various channel models. The simulation study shows that this approach gives better performance over training-based channel estimation (TBCE) and OPML SBCE methods but at the cost of higher computational complexity.

Guaranteed Minimization of the Bit Error Ratio for MIMO Systems: A Mathematical Viewpoint

2021 ◽  
Author(s):  
Ekaterina Auer ◽  
Andreas Ahrens
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Point Of View ◽  
Error Ratio ◽  
Multiple Input ◽  
Bit Error Ratio ◽  
Communication Links ◽  
Input Multiple Output ◽  
Wireless Standards ◽  
Formal Point

Abstract Multiplying the capacity of communication links by using the multiple-input multiple-output mechanism has become an essential part of various wireless standards. In this paper, we focus on the bit error rate in such systems and consider its optimization under parameter uncertainty from a formal point of view (including methods with result verification). The theoretical results are demonstrated using a close-to-life application.

Design and Implementation of a Low-Complexity Multiuser Vector Precoder

2012 ◽  
Vol 3 (1) ◽  
pp. 31-48 ◽  
Author(s):  
Maitane Barrenechea ◽  
Luis Barbero ◽  
Mikel Mendicute ◽  
John S. Thompson
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Performance Loss ◽  
Dirty Paper Coding ◽  
Multiple Input ◽  
Input Multiple Output ◽  
The Cost ◽  
Complexity Constraints ◽  
Novel Design

Precoding techniques are used in the downlink of multiuser multiple-input multiple-output (MIMO) systems in order to separate the information data streams aimed at scattered user terminals. Vector precoding (VP) is one of the most promising non-linear precoding schemes, which achieves a performance close to the optimum albeit impractical dirty paper coding (DPC) with a feasible complexity. This contribution presents a novel design for the hardware implementation of a high-throughput vector precoder based on the Fixed Sphere Encoder (FSE) algorithm. The proposed fixed-complexity scheme greatly reduces the complexity of the most intricate part of VP, namely the search for the perturbing signal in an infinite lattice. Additionally, an optimized reduced-complexity implementation is presented which considerably reduces the resource usage at the cost of a small performance loss. Provided simulation results show the better performance of the proposed vector precoder in comparison to other fixed-complexity approaches, such as the K-Best precoder, under similar complexity constraints.

scholarly journals A novel signal detection algorithm of multiple-input multiple-output Vertical-Bell Laboratories Layered Space-Time for underwater acoustic networks based on the improved minimum mean square error

2020 ◽  
Vol 16 (12) ◽  
pp. 155014772097989
Author(s):  
Gaoli Zhao ◽  
Jianping Wang ◽  
Junping Song ◽  
Wei Chen
Keyword(s):  
Energy Consumption ◽  
Multiple Input Multiple Output ◽  
Space Time ◽  
Underwater Acoustic ◽  
Error Ratio ◽  
Acoustic Networks ◽  
Multiple Input ◽  
Bit Error Ratio ◽  
Input Multiple Output ◽  
Underwater Acoustic Networks

Multiple-input multiple-output is a commonly used technology supporting for high-rate transmission over frequency-selective fading channels with multiple antennas. Vertical-Bell Laboratories Layered Space-Time is a detection method of a multiple-input multiple-output system, which establishes a direct correspondence between antennas and layers. Studies demonstrate that multiple-input multiple-output Vertical-Bell Laboratories Layered Space-Time is a meaningful way for underwater acoustic networks of high performance. However, considering the hardware constraints and energy consumption, achieving a trade-off between the bit error ratio and complexity is a crucial issue for underwater acoustic networks of multiple-input multiple-output Vertical-Bell Laboratories Layered Space-Time systems. This article proposes a novel signal detection algorithm of multiple-input multiple-output Vertical-Bell Laboratories Layered Space-Time. First, we address the unitary matrix of the underwater acoustic channel by LDLH decomposition. Second, we order the detection sequence based on the permutation matrix. Third, we detail the implementation of interference cancelation and slice processing. Finally, we perform experiments for comparing the bit error ratio, energy consumption, processing delay, and complexity of the proposed algorithm with zero-forcing Vertical-Bell Laboratories Layered Space-Time, minimum mean square error Vertical-Bell Laboratories Layered Space-Time, and maximum likelihood Vertical-Bell Laboratories Layered Space-Time. Results indicate that our algorithm maintains bit error ratio and the processing delay to that of maximum likelihood Vertical-Bell Laboratories Layered Space-Time algorithm. However, it reduces the energy consumption, which achieves a good trade-off between performance and complexity. This work supports on constructing underwater acoustic networks of multiple-input multiple-output Vertical-Bell Laboratories Layered Space-Time system.

New multiple-input multiple-output-based filter bank multicarrier structure for cognitive radio networks

2019 ◽  
Vol 13 (10) ◽  
pp. 1514-1523
Author(s):  
Zahraa Abd El-Hamid ◽  
Emad S. Hassan ◽  
Abdel-Halim A. Zekry ◽  
Salah S. Elagooz ◽  
Moataz Samir ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Filter Bank ◽  
Multiple Input Multiple Output ◽  
Radio Networks ◽  
Filter Bank Multicarrier ◽  
Multiple Input ◽  
Input Multiple Output

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.

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