scholarly journals Hardware Implementation and Performance Analysis of Improved Sphere Decoder in Spatially Correlated Massive MIMO Channels

2021 ◽  
Author(s):  
Dimitris Vordonis ◽  
Vassilis Paliouras
Keyword(s):  
Massive Mimo ◽  
Large Scale ◽  
Hardware Implementation ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Mimo Channels ◽  
Sphere Decoder ◽  
Trade Offs ◽  
Simulation Results ◽  
The Impact

Detection for high-dimensional multiple-input multiple-output (MIMO) and massive MIMO (MMIMO) systems is an active field of research in wireless communications. While most works consider spatially uncorrelated channels, practical MMIMO channels are correlated. This paper investigates the impact of correlation on Sphere Decoder (SD), for both single-user (SU) and multi-user (MU) scenarios. The complexity of SD is mainly determined by the initial radius (IR) method and the number of visited nodes during detection. This paper employs an efficient IR and proposes a new metric constraint in the tree searching algorithm, that significantly decrease the number of visited nodes and render SD feasible for large-scale systems. In addition, an introduced hardware implementation featured with a one-node-per-cycle architecture, minimizes the latency of the detection process. Trade-offs between bit error rate (BER) performance and computational complexity are presented. The trade-offs are achieved by either modifying the backtracking mechanism or limiting the number of radius updates. Simulation results prove that the proposed optimizations are effective for both correlated and uncorrelated channels, regardless of the level of noise. The decoding gain of SD compared to the low-complexity linear detectors (LD) is higher in the presence of correlation than in the uncorrelated case. However, as expected, spatial correlation adversely affects the performance and the complexity of SD. Simulation results reported here also confirm that correlation at the side equipped with more antennas is less detrimental. Hardware implementation aspects are examined for both a Virtex-7 FPGA device and a 28-nm ASIC technology.<br>

scholarly journals Hardware Implementation and Performance Analysis of Improved Sphere Decoder in spatially correlated Massive MIMO channels

2021 ◽  
Author(s):  
Dimitris Vordonis ◽  
Vassilis Paliouras
Keyword(s):  
Massive Mimo ◽  
Large Scale ◽  
Hardware Implementation ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Mimo Channels ◽  
Sphere Decoder ◽  
Trade Offs ◽  
Simulation Results ◽  
The Impact

<div>Detection for high-dimensional multiple-input multiple-output (MIMO) and Massive MIMO (MMIMO) systems is an active field of research in wireless communications. While most works consider spatially uncorrelated channels, practical MMIMO channels are correlated. This paper investigates the impact of correlation on Sphere Decoder (SD), not only for Single-User (SU) but also for Multi-User (MU) scenarios. The complexity of SD is mainly determined by the Initial Radius (IR) method and the number of visited nodes during detection. This paper proposes both an efficient IR and a new metric constraint in the tree searching algorithm, that significantly decrease the number of visited nodes and render SD feasible for large-scale systems. In addition, a hardware implementation featured with a one-node-per-cycle architecture, minimizes the latency of the detection process. Trade-offs between bit error rate (BER) performance and computational complexity are presented, either modifying the backtracking mechanism or limiting the number of radius updates. Simulation results prove that the proposed optimizations are effective for both correlated and uncorrelated channels, regardless the level of noise. The decoding gain of SD compared to the low-complexity Linear Detectors (LD) is higher in the presence of correlation than in the uncorrelated case. However, as expected, spatial correlation adversely affects the performance and the complexity of SD. Simulation results reported here also confirm that correlation at the side equipped with more antennas is less detrimental. Hardware aspects are examined for both a Virtex-7 FPGA device and a 28-nm ASIC technology.</div>

scholarly journals Hardware Implementation and Performance Analysis of Improved Sphere Decoder in spatially correlated Massive MIMO channels

2021 ◽  
Author(s):  
Dimitris Vordonis ◽  
Vassilis Paliouras
Keyword(s):  
Massive Mimo ◽  
Large Scale ◽  
Hardware Implementation ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Mimo Channels ◽  
Sphere Decoder ◽  
Trade Offs ◽  
Simulation Results ◽  
The Impact

<div>Detection for high-dimensional multiple-input multiple-output (MIMO) and Massive MIMO (MMIMO) systems is an active field of research in wireless communications. While most works consider spatially uncorrelated channels, practical MMIMO channels are correlated. This paper investigates the impact of correlation on Sphere Decoder (SD), not only for Single-User (SU) but also for Multi-User (MU) scenarios. The complexity of SD is mainly determined by the Initial Radius (IR) method and the number of visited nodes during detection. This paper proposes both an efficient IR and a new metric constraint in the tree searching algorithm, that significantly decrease the number of visited nodes and render SD feasible for large-scale systems. In addition, a hardware implementation featured with a one-node-per-cycle architecture, minimizes the latency of the detection process. Trade-offs between bit error rate (BER) performance and computational complexity are presented, either modifying the backtracking mechanism or limiting the number of radius updates. Simulation results prove that the proposed optimizations are effective for both correlated and uncorrelated channels, regardless the level of noise. The decoding gain of SD compared to the low-complexity Linear Detectors (LD) is higher in the presence of correlation than in the uncorrelated case. However, as expected, spatial correlation adversely affects the performance and the complexity of SD. Simulation results reported here also confirm that correlation at the side equipped with more antennas is less detrimental. Hardware aspects are examined for both a Virtex-7 FPGA device and a 28-nm ASIC technology.</div>

scholarly journals A Robust Hybrid Iterative Linear Detector for Massive MIMO Uplink Systems

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 306 ◽  
Author(s):  
Mahmoud A. Albreem ◽  
Mohammed H. Alsharif ◽  
Sunghwan Kim
Keyword(s):  
Computational Complexity ◽  
Convergence Rate ◽  
Massive Mimo ◽  
High Performance ◽  
Large Scale ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Initial Vector ◽  
High Data

Fifth-generation (5G) communications system is commercially introduced by several mobile operators where sub-6 GHz bands are the backbone of the 5G networks. A large-scale multiple-input multiple-output (MIMO), or massive MIMO (mMIMO), technology has a major impact to secure high data rate, high spectral efficiency, and quality of service (QoS). It could also have a major role in the beyond-5G systems. A massive number of antennas seek advanced signal processing to detect and equalize the signal. However, optimal detectors, such as the maximum likelihood (ML) and maximum posterior (MAP), are not desirable in implementation due to extremely high complexity. Therefore, sub-optimum solutions have been introduced to obtain and guarantee enough balance between the performance and the computational complexity. In this paper, a robust and joint low complexity detection algorithm is proposed based on the Jacobi (JA) and Gauss–Seidel (GS) methods. In such iterative methods, the performance, complexity, and convergence rate are highly dependent on the initial vector. In this paper, initial solution is proposed by exploiting the benefits of a stair matrix to obtain a fast convergence rate, high performance, and low complexity. Numerical results show that proposed algorithm achieves high accuracy and relieve the computational complexity even when the BS-to-user-antenna ratio (BUAR) is small.

scholarly journals Robust Hybrid Beamforming Scheme for Millimeter-Wave Massive-MIMO 5G Wireless Networks

Symmetry ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1424 ◽  
Author(s):  
Saleem Latteef Mohammed ◽  
Mohammed H. Alsharif ◽  
Sadik Kamel Gharghan ◽  
Imran Khan ◽  
Mahmoud Albreem
Keyword(s):  
Wireless Networks ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Large Scale ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Network Capacity ◽  
System Throughput ◽  
Hybrid Beamforming

Wireless networks employing millimeter-wave (mmWave) and Massive Multiple-Input Multiple-Output (MIMO) technologies are a key approach to boost network capacity, coverage, and quality of service (QoS) for future communications. They deploy symmetric antennas on a large scale in order to enhance the system throughput and data rate. However, increasing the number of antennas and Radio Frequency (RF) chains results in high computational complexity and more energy requirements. Therefore, to solve these problems, this paper proposes a low-complexity hybrid beamforming scheme for mmWave Massive-MIMO 5G wireless networks. The proposed algorithm is on the basis of alternating the minimum mean square error (Alt-MMSE) hybrid beamforming technique in which the orthogonal properties of the digital matrix were designed, and then the MSE of the transmitted and received signal was reduced. The phase of the analog matrix was obtained from the updated digital matrix. Simulation results showed that the proposed hybrid beamforming algorithm had better performance than existing state-of-the-art algorithms, and similar performance with the optimal digital precoding algorithm.

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.

scholarly journals Data Detection in Single User Massive MIMO Using Re-Transmissions

2019 ◽  
Vol 6 (1) ◽  
pp. 15-26 ◽  
Author(s):  
K. Vasudevan ◽  
K. Madhu ◽  
Shivani Singh
Keyword(s):  
Massive Mimo ◽  
Turbo Code ◽  
Additive White Gaussian Noise ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Base Station ◽  
Mimo Channel ◽  
Data Detection ◽  
Major Drawback ◽  
Single User

Background:Single user Massive Multiple Input Multiple Output (MIMO) can be used to increase the spectral efficiency since the data is transmitted simultaneously from a large number of antennas located at both the base station and mobile. It is feasible to have a large number of antennas in the mobile, in the millimeter wave frequencies. However, the major drawback of single user massive MIMO is the high complexity of data recovery at the receiver.Methods:In this work, we propose a low complexity method of data detection with the help of re-transmissions. A turbo code is used to improve the Bit-Error-Rate (BER).Results and Conclusion:Simulation results indicate a significant improvement in BER with just two re-transmissions as compared to the single transmission case. We also show that the minimum average SNR per bit required for error-free propagation over a massive MIMO channel with re-transmissions is identical to that of the Additive White Gaussian Noise (AWGN) channel, which is equal to -1.6 dB.

Influence of Oriented Perforation Design on Refracture Reorientation: Simulation and Experiment

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
Minhui Qi ◽  
Mingzhong Li ◽  
Tiankui Guo ◽  
Chunting Liu ◽  
Song Gao ◽  
...  
Keyword(s):  
Hydraulic Fracturing ◽  
Large Scale ◽  
Simulation Models ◽  
Fracture Initiation ◽  
Simulation Method ◽  
Induced Stress ◽  
Study Results ◽  
Simulation Results ◽  
Fracturing Experiments ◽  
The Impact

The oriented perforating is the essential technique to guide the refracture reorientation, but the influence of the oriented perforation design on the refracture steering radius is still unclear. In this paper, the factors influencing the refracture reorientation were studied by simulation models and experiments. The effects of initial fracture, well production, and perforations on the refracture initiation and propagation were analyzed. Three-dimensional finite element models were conducted to quantify the impact of perforation depth, density, and azimuth on the refracture. The large-scale three-axis hydraulic fracturing experiments guided by oriented perforations were also carried out to verify the fracture initiation position and propagation pattern of the simulation results. The research results showed that perforations change the near-wellbore induced stress distribution, thus changing the steering radius of the refracture. According to the simulation results, the oriented perforation design has a significant influence on the perforation guidance effect and refracture characteristics. Five hydraulic fracturing experiments proved the influence of perforating parameters on fracture initiation and morphology, which have a right consistency between the simulation results. This paper presents a numerical simulation method for evaluating the influence of the refracture reorientation characteristics under the consideration of multiple prerefracturing induced-stress and put forward the oriented perforation field design suggestions according to the study results.

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.

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