scholarly journals Efficient Detectors based on Group Detection for Massive MIMO systems

2018 ◽  
Author(s):  
Thanh-Binh Nguyen ◽  
Minh-Tuan Le ◽  
Vu-Duc Ngo ◽  
Tien-Dong Nguyen ◽  
Huy-Dung Han
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Bell Laboratory ◽  
Channel Matrix ◽  
Input Multiple Output ◽  
Group Detection ◽  
Ber Performance

In Multiple Input Multiple Output (MIMO) systems, the complexities of detectors depend on the size of the channel matrix. In Massive MIMO systems, detection complexity becomes remarkably higher because the dimensions of the channel matrix get much larger. In order to recover the signals in the up-link of a Massive MIMO system at reduced complexities, we first divide the system into two sub-systems. After that, we apply the Minimum Mean Square Error (MMSE) and Bell Laboratory Layer Space Time (BLAST) detectors to each subsystem, resulting in the so-called MMSE-GD and BLAST-GD detectors, respectively. To further enhance the BER performance of Massive MIMO systems under the high-load conditions, we propose two additional detectors, called MMSE-IGD and BLAST-IGD by respectively applying the conventional MMSE and BLAST on the sub-systems in an iterative manner. It is shown via computer simulation and analytical results that the proposed detectors enable the system to achieve not only higher BER performance but also low detection complexities as compared to the conventional linear detectors. Moreover, the MMSE-IGD and BLAST-IGD can significantly improve BER performance of Massive MIMO systems.

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 An Improved Jacobi-Based Detector for Massive MIMO Systems

Information ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 165 ◽  
Author(s):  
Xiaoqing Zhao ◽  
Zhengquan Li ◽  
Song Xing ◽  
Yang Liu ◽  
Qiong Wu ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Correction Method ◽  
Detection Algorithm ◽  
Detection Accuracy ◽  
Input Multiple Output ◽  
Mmse Detector

Massive multiple-input-multiple-output (MIMO) is one of the key technologies in the fifth generation (5G) cellular communication systems. For uplink massive MIMO systems, the typical linear detection such as minimum mean square error (MMSE) presents a near-optimal performance. Due to the required direct matrix inverse, however, the MMSE detection algorithm becomes computationally very expensive, especially when the number of users is large. For achieving the high detection accuracy as well as reducing the computational complexity in massive MIMO systems, we propose an improved Jacobi iterative algorithm by accelerating the convergence rate in the signal detection process.Specifically, the steepest descent (SD) method is utilized to achieve an efficient searching direction. Then, the whole-correction method is applied to update the iterative process. As the result, the fast convergence and the low computationally complexity of the proposed Jacobi-based algorithm are obtained and proved. Simulation results also demonstrate that the proposed algorithm performs better than the conventional algorithms in terms of the bit error rate (BER) and achieves a near-optimal detection accuracy as the typical MMSE detector, but utilizing a small number of iterations.

scholarly journals Signal Detection Based on Parallel Group Detection Algorithm for High-Load Massive MIMO Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Thanh-Binh Nguyen ◽  
Minh-Tuan Le ◽  
Vu-Duc Ngo
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Detection Algorithm ◽  
High Load ◽  
Signal Recovery ◽  
Parallel Group ◽  
Group Detection ◽  
Practical Complexity ◽  
Ber Performance

In this paper, a parallel group detection (PGD) algorithm is proposed in order to address the degradation in the bit error rate (BER) performance of linear detectors when they are used in high-load massive MIMO systems. The algorithm is constructed by converting the equivalent extended massive MIMO system into two subsystems, which can be simultaneously detected by the classical detection procedures. Then, using the PGD and the classical ZF as well as the QR-decomposition- (QRD-) based detectors, we proposed two new detectors, called ZF-based PGD (ZF-PGD) and QRD-based PGD (QRD-PGD). The PGD is further combined with the sorted longest basis (SLB) algorithm to make the signal recovery more accurate, thereby resulting in two new detectors, namely, the ZF-PGD-SLB and the QRD-PGD-SLB. Various complexity evaluations and simulations prove that the proposed detectors can significantly improve the BER performance compared to their classical linear and QRD counterparts with the practical complexity levels. Hence, our proposed detectors can be used as efficient means of estimating the transmitted signals in high-load massive MIMO systems.

scholarly journals Pilot Decontamination Using Asynchronous Fractional Pilot Scheduling in Massive MIMO Systems

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6213
Author(s):  
Muhammad Irshad Zahoor ◽  
Zheng Dou ◽  
Syed Bilal Hussain Shah ◽  
Imran Ullah Khan ◽  
Sikander Ayub ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ideal Number ◽  
Sum Rate ◽  
Inter Cell Interference ◽  
Time Division

Due to large spectral efficiency and low power consumption, the Massive Multiple-Input-Multiple-Output (MIMO) became a promising technology for the 5G system. However, pilot contamination (PC) limits the performance of massive MIMO systems. Therefore, two pilot scheduling schemes (i.e., Fractional Pilot Reuse (FPR) and asynchronous fractional pilot scheduling scheme (AFPS)) are proposed, which significantly mitigated the PC in the uplink time division duplex (TDD) massive MIMO system. In the FPR scheme, all the users are distributed into the central cell and edge cell users depending upon their signal to interference plus noise ratio (SINR). Further, the capacity of central and edge users is derived in terms of sum-rate, and the ideal number of the pilot is calculated which significantly maximized the sum rate. In the proposed AFPS scheme, the users are grouped into central users and edge users depending upon the interference they receive. The central users are assigned the same set of pilots because these users are less affected by interference, while the edge users are assigned the orthogonal pilots because these users are severely affected by interference. Consequently, the pilot overhead is reduced and inter-cell interference (ICI) is minimized. Further, results verify that the proposed schemes outperform the previous proposed traditional schemes, in terms of improved sum rates.

scholarly journals Massive MIMO Systems for 5G

2020 ◽  
Author(s):  
Robin Chataut ◽  
Robert Akl
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Visible Light Communication ◽  
User Scheduling ◽  
Access Technology ◽  
Input Multiple Output ◽  
Simple Processing

The global bandwidth shortage in the wireless communication sector has motivated the study and exploration of wireless access technology known as massive Multiple-Input Multiple-Output (MIMO). Massive MIMO is one of the key enabling technology for next-generation networks, which groups together antennas at both transmitter and the receiver to provide high spectral and energy efficiency using relatively simple processing. Obtaining a better understating of the massive MIMO system to overcome the fundamental issues such as pilot contamination, channel estimation, precoding, user scheduling, energy efficiency, and signal detection is vital for the successful deployment of 5G and beyond networks. Some of the recent trends in massive MIMO are terahertz communication, ultra massive MIMO (UM-MIMO), visible light communication (VLC), machine learning, and deep learning. 

Improved Port Modulation for Multiuser Massive MIMO Systems

2015 ◽  
Vol 7 (4) ◽  
pp. 15-25
Author(s):  
Yujiao He ◽  
Jianing Zhao ◽  
Lijuan Tao ◽  
Fuyu Hou ◽  
Wei Jia
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Channel State ◽  
State Information ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Simulation Results ◽  
Csi Feedback

This paper proposes an improved port modulation (PM) method which can be applied to the multiuser (MU) massive multiple-input multiple-output (MIMO) system. The precoding process of the improved PM can be divided into two parts: port precoding and MU precoding. The methods of the precoding and detection are provided and the performance of the proposed improved PM is simulated and analyzed. Simulation results show that the proposed improved PM system can achieve a satisfying bit error rate (BER) performance with a cutdown channel state information (CSI) feedback.

scholarly journals BER Performance Evaluation of Turbo Coded MIMO System in Nakagami Channel

2019 ◽  
Vol 8 (12) ◽  
pp. 5101-5104
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Data Communication ◽  
Block Codes ◽  
Space Time Block Codes ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Improved Performance ◽  
Ber Performance

Wireless technologies are aiming to improve data rates along with reliability using Multiple Input and Multiple Output(MIMO) systems. The major performance parameter for advanced systems is Bit Error rate (BER). Researchers are working for minimizing the BER for data communication. This paper presents the BER performance of turbo coded Multiple Input Multiple Output (MIMO) system in Nakagami channel. MIMO system is realized using Space Time Block Codes. System performance is analyzed for M-ary Quadrature Amplitude Modulation (QAM) in Nakagami channel. System is implemented using MATLAB code. 4QAM system performs better as far as BER is concerned. The implemented turbo coded system outperforms the uncoded system in case of BER performance. This system can be used for improved performance of data communication in LTE and WiMax.

scholarly journals Low-complexity sparse-aware multiuser detection for large-scale MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rong Ran ◽  
Hayoung Oh
Keyword(s):  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Finite Alphabet ◽  
Multiuser Detectors ◽  
Input Multiple Output ◽  
Error Detector ◽  
Significant Performance

AbstractSparse-aware (SA) detectors have attracted a lot attention due to its significant performance and low-complexity, in particular for large-scale multiple-input multiple-output (MIMO) systems. Similar to the conventional multiuser detectors, the nonlinear or compressive sensing based SA detectors provide the better performance but are not appropriate for the overdetermined multiuser MIMO systems in sense of power and time consumption. The linear SA detector provides a more elegant tradeoff between performance and complexity compared to the nonlinear ones. However, the major limitation of the linear SA detector is that, as the zero-forcing or minimum mean square error detector, it was derived by relaxing the finite-alphabet constraints, and therefore its performance is still sub-optimal. In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems. The proposed SDSB-SA detector adheres to the finite-alphabet constraints so that it outperforms the conventional linear SA detector, in particular, in high SNR regime. Meanwhile, the proposed detector follows a single-dimensional search manner, so it has a very low computational complexity which is feasible for light-ware Internet of Thing devices for ultra-reliable low-latency communication. Numerical results show that the the proposed SDSB-SA detector provides a relatively better tradeoff between the performance and complexity compared with several existing detectors.

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.

PROBLEM STATEMENT OF JOINT ANTENNA SELECTION AND PRECODING IN MASSIVE MIMO COMMUNICATION SYSTEMS

2021 ◽  
Author(s):  
В.Б. КРЕЙНДЕЛИН ◽  
М.В. ГОЛУБЕВ
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Research Areas ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Legal Restrictions ◽  
Multiple Transmission

Совместный с прекодингом автовыбор антенн на приемной и передающей стороне - одно из перспективных направлений исследований для реализации технологий Multiple Transmission and Reception Points (Multi-TRP, множество точек передачи и приема) в системах со многими передающими и приемными антеннами Massive MIMO (Multiple-Input-Multiple-Output), которые активно развиваются в стандарте 5G. Проанализированы законодательные ограничения, влияющие на применимость технологий Massive MIMO, и специфика реализации разрабатываемого алгоритма в миллиметровомдиапа -зоне длин волн. Рассмотрены алгоритмы формирования матриц автовыбора антенн как на передающей, так и на приемной стороне. Сформулирована строгая математическая постановка задачи для двух критериев работы алгоритма: максимизация взаимной информации и минимизация среднеквадратичной ошибки. Joint precoding and antenna selection both on transmitter and receiver sides is one of the promising research areas for evolving toward the Multiple Transmission and Reception Points (Multi-TRP) concept in Massive MIMO systems. This technology is under active development in the coming 5G 3GPP releases. We analyze legal restrictions for the implementation of 5G Massive MIMO technologies in Russia and the specifics of the implementation of the developed algorithm in the millimeter wavelength range. Algorithms of antenna auto-selection matrices formation on both transmitting and receiving sides are considered. Two criteria are used for joint antenna selection and precoding: maximizing mutual information and minimizing mean square error.

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