scholarly journals Partial Nulling Regularized Block Diagonalization Using Unfair Channel Selection for Post-Coding with Low-Complexity

2020 ◽  
Vol 10 (19) ◽  
pp. 6809
Author(s):  
Hyun-Sun Hwang ◽  
Jae-Hyun Ro ◽  
Young-Hwan You ◽  
Duckdong Hwang ◽  
Hyoung-Kyu Song
Keyword(s):  
Performance Enhancement ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Diversity Gain ◽  
Block Diagonalization ◽  
Time Diversity ◽  
Multiple Input ◽  
Input Multiple Output ◽  
User Interference

A number of requirements for 5G mobile communication are satisfied by adopting multi-user multiple input multiple output (MU-MIMO) systems. The inter user interference (IUI) which is an inevitable problem in MU-MIMO systems becomes controllable when the precoding scheme is used. The proposed scheme, which is one of the precoding schemes, is built on regularized block diagonalization (RBD) precoding and utilizes the partial nulling concept, which is to leave part of the IUI at the same time. Diversity gain is obtained by leaving IUI, which is made by choosing the row vectors of the channel matrix that are not nullified. Since the criterion for choosing the row vectors of the channel is the power of the channel, the number of selected row vectors of the channel for each device can be unfair. The proposed scheme achieves performance enhancement by obtaining diversity gain. Therefore, the bit error rate (BER) performance is better and the computational complexity is lower than RBD when the same data rate is achieved. When the number of reduced data streams is not enough for most devices to achieve diversity gain, the proposed scheme has better performance compared to generalized block diagonalization (GBD). The low complexity at the receiver is achieved compared to GBD by using the simple way to remove IUI.

scholarly journals Early Neighbor Rejection-Aided Tabu Search Detection for Large MIMO Systems

2021 ◽  
Vol 11 (16) ◽  
pp. 7305
Author(s):  
Uzokboy Ummatov ◽  
Jin-Sil Park ◽  
Gwang-Jae Jang ◽  
Ju-Dong Lee
Keyword(s):  
Computational Complexity ◽  
Tabu Search ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Qr Decomposition ◽  
Efficient Computation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ordering Schemes

In this study, a low complexity tabu search (TS) algorithm for multiple-input multiple-output (MIMO) systems is proposed. To reduce the computational complexity of the TS algorithm, early neighbor rejection (ENR) and layer ordering schemes are employed. In the proposed ENR-aided TS (ENR-TS) algorithm, the least promising k neighbors are excluded from the neighbor set in each layer, which reduces the computational complexity of neighbor examination in each TS iteration. For efficient computation of the neighbors’ metrics, the ENR scheme can be incorporated into QR decomposition-aided TS (ENR-QR-TS). To further reduce the complexity and improve the performance of the ENR-QR-TS scheme, a layer ordering scheme is employed. The layer ordering scheme determines the order in which layers are detected based on their expected metrics, which reduces the risk of excluding likely neighbors in early layers. The simulation results show that the ENR-TS achieves nearly the same performance as the conventional TS while providing up to 82% complexity reduction.

scholarly journals Massive MIMO, mmWave and mmWave-Massive MIMO Communications: Performance Assessment with Beamforming Techniques

2020 ◽  
Author(s):  
Tewelgn Kebede Engda ◽  
Yihenew Wondie ◽  
Johannes Steinbrunn
Keyword(s):  
Mobile Networks ◽  
Massive Mimo ◽  
Performance Metrics ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Fifth Generation ◽  
Emerging Trends ◽  
Multiple Input ◽  
Input Multiple Output

Abstract A considerable amount of enabling technologies are being explored in the era of fifth generation (5G) mobile system. The dream is to build a wireless network that substantially improves the existing mobile networks in all performance metrics. To address this 5G design targets, massive MIMO (multiple input multiple output) and mmWave (millimeter wave) communication are also candidate technologies. Luckily, in many respects these two technologies share a symbiotic integration. Accordingly, a logical step is to integrate mmWave communications and massive MIMO to form mmWave-massive MIMO which substantially increases user throughput, improve spectral and energy efficiencies, increase the capacity of mobile networks and achieve high multiplexing gains. Thus, this work analyses the concepts, performances, comparison and discussion of these technologies called: massive MIMO, mmWave Communications and mmWave-massive MIMO systems jointly. Besides, outcomes of extensive researches, emerging trends together with their respective benefits, challenges, proposed solutions and their comparative analysis is addressed. The performance of hybrid analog-digital beamforming architecture with a fully digital and analog beamforming techniques are also analyzed. Analytical and simulation results show that the low-complexity hybrid analog-digital precoding achieves all round comparable precoding gains for mmWave-Massive MIMO technology.

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 Impact of Stair and Diagonal Matrices in Iterative Linear Massive MIMO Uplink Detectors for 5G Wireless Networks

Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 71 ◽  
Author(s):  
Mahmoud A. Albreem ◽  
Mohammed H. Alsharif ◽  
Sunghwan Kim
Keyword(s):  
Computational Complexity ◽  
Iterative Methods ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Matrix Inversion ◽  
Multiple Input ◽  
The Matrix ◽  
Input Multiple Output ◽  
The Impact

In massive multiple-input multiple-output (M-MIMO) systems, a detector based on maximum likelihood (ML) algorithm attains optimum performance, but it exhaustively searches all possible solutions, hence, it has a very high complexity and realization is denied. Linear detectors are an alternative solution because of low complexity and simplicity in implementation. Unfortunately, they culminate in a matrix inversion that increases the computational complexity in high loaded systems. Therefore, several iterative methods have been proposed to approximate or avoid the matrix inversion, such as the Neuamnn series (NS), Newton iterations (NI), successive overrelaxation (SOR), Gauss–Siedel (GS), Jacobi (JA), and Richardson (RI) methods. However, a detector based on iterative methods requires a pre-processing and initialization where good initialization impresses the convergence, the performance, and the complexity. Most of the existing iterative linear detectors are using a diagonal matrix ( D ) in initialization because the equalization matrix is almost diagonal. This paper studies the impact of utilizing a stair matrix ( S ) instead of D in initializing the linear M-MIMO uplink (UL) detector. A comparison between iterative linear M-MIMO UL detectors with D and S is presented in performance and computational complexity. Numerical Results show that utilization of S achieves the target performance within few iterations, and, hence, the computational complexity is reduced. A detector based on the GS and S achieved a satisfactory bit-error-rate (BER) with the lowest complexity.

Efficient Antenna Selection in MIMO Correlated Channels

2012 ◽  
Vol 429 ◽  
pp. 242-248
Author(s):  
Guo Yan Li ◽  
You Guang Zhang
Keyword(s):  
Mimo Systems ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Channel State ◽  
Spatially Correlated ◽  
Correlated Channels ◽  
Spatially Correlated Channels ◽  
Multiple Input ◽  
Input Multiple Output

Multiple-input multiple-output (MIMO) systems can bring many advantages to wireless communication but suffer from high cost and complexity due to the multiple RF chains. In such systems, antenna selection is introduced as a technique to ease these problems.This paper addressedthe problem of antenna selection in spatially correlated channels. We propose an effective antenna selection method in terms of capacity maximization based on the transmit and/or the receive correlation matrix instead of the instantaneous channel state information (ICSI).Simulations will be used to validate our analysis and demonstrate that the number of required RF chains can be significantly decreased using our low complexity algorithm whileachieving very close performance to the ICSI-based method.

scholarly journals Enhancement of Twice Quasi Orthogonal Space Time Block Coded (QOSTBC) Performance System with Zero Forcing EVCM Decoder

2018 ◽  
Vol 218 ◽  
pp. 03009
Author(s):  
Desy Agustin ◽  
Nachwan Mufti Adriansyah ◽  
Muhsin
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
High Reliability ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Space Time ◽  
Zero Forcing ◽  
Receiver Diversity ◽  
Multiple Input ◽  
Input Multiple Output

In today’s modern telecommunications systems, makes the number of studies and development of multiple antennas and multiple-input multiple-output (MIMO) systems to achieve high reliability and low complexity. One attractive approach to improve that performance is using technique transmit diversity which is spacetime block coding and receiver diversity i.e. zero forcing EVCM (ZF EVCM). Although some earlier MIMO standards were develop some space-time codes like (O-STBC)and (Q-OSTBC) to provide high reliability but they are limited able to achieve orthogonality. In this research will be proposed a MIMO system scheme which is an improvement of QOSTBC that used a transmission diversity technique. This improvement from QOSTBC is Twice QOSTBC uses a provision in two codeword matrices to be sent are arranged diagonally so as to have higher levels of orthogonality. In this case Twice QOSTBC highly structured (4x1) can be replaced as an equivalent EVCM channel H. The proposed Twice-QOSTBC’s results outperform other QOSTBC techniques with a difference around 3 dB for single-input multi-input (MISO) input configuration at 10-6 BER and receiver ZF EVCM has a very similar structure as the code matrix S of the underlying Twice QSTBC which can eliminates the system complexity.

scholarly journals A Low Complexity Channel Estimation and Detection for Massive MIMO Using SC-FDE

Telecom ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 3-17
Author(s):  
Mário Marques da Silva ◽  
Rui Dinis ◽  
João Guerreiro
Keyword(s):  
Channel Estimation ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Data Detection ◽  
Pilot Symbols ◽  
Multiple Input ◽  
Input Multiple Output

5G Communications will support millimeter waves (mm-Wave), alongside the conventional centimeter waves, which will enable much higher throughputs and facilitate the employment of hundreds or thousands of antenna elements, commonly referred to as massive Multiple Input–Multiple Output (MIMO) systems. This article proposes and studies an efficient low complexity receiver that jointly performs channel estimation based on superimposed pilots, and data detection, optimized for massive MIMO (m-MIMO). Superimposed pilots suppress the overheads associated with channel estimation based on conventional pilot symbols, which tends to be more demanding in the case of m-MIMO, leading to a reduction in spectral efficiency. On the other hand, MIMO systems tend to be associated with an increase of complexity and increase of signal processing, with an exponential increase with the number of transmit and receive antennas. A reduction of complexity is obtained with the use of the two proposed algorithms. These algorithms reduce the complexity but present the disadvantage that they generate a certain level of interference. In this article, we consider an iterative receiver that performs the channel estimation using superimposed pilots and data detection, while mitigating the interference associated with the proposed algorithms, leading to a performance very close to that obtained with conventional pilots, but without the corresponding loss in the spectral efficiency.

scholarly journals Low-complexity signal detection and precoding algorithms for multiuser massive MIMO systems

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Abdelhak Boukharouba ◽  
Marwa Dehemchi ◽  
Asma Bouhafer
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Matrix Decomposition ◽  
Low Complexity ◽  
Zero Forcing ◽  
Wireless System ◽  
Efficient Detection ◽  
Large Matrix ◽  
Multiple Input ◽  
Input Multiple Output

AbstractIn this study, we present efficient detection and precoding algorithms for massive multi-user multiple-input multiple-output wireless system. To reduce the computational complexity due to large matrix inversion, the proposed algorithms are an enhanced version of zero forcing scheme based on QR matrix decomposition for both uplink and downlink systems. Through extensive numerical experiments, we demonstrate that the proposed algorithms outperform the recently published ones in terms of performance and complexity.

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.

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