scholarly journals Normalized Structured Compressed Sensing Based Signal Detection in Spatial Modulation 3D-MIMO Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Wei Ren ◽  
Guan Gui ◽  
Fei Li
Keyword(s):  
Compressed Sensing ◽  
Signal Detection ◽  
Communication Systems ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Iteration Process ◽  
High Energy ◽  
Spatial Modulation ◽  
3D Mimo

Signal detection is one of the fundamental problems in three-dimensional multiple-input multiple-output (3D-MIMO) wireless communication systems. This paper addresses a signal detection problem in 3D-MIMO system, in which spatial modulation (SM) transmission scheme is considered due to its advantages of low complexity and high-energy efficiency. SM based signal transmission typically results in the block-sparse structure in received signals. Hence, structured compressed sensing (SCS) based signal detection is proposed to exploit the inherent block sparsity information in the received signal for the uplink (UL). Moreover, normalization preprocessing is considered before iteration process with the purpose of preventing the noise from being overamplified by the column vector with inadequately large elements. Simulation results are provided to show the stable and reliable performance of the proposed algorithm under both Gaussian and non-Gaussian noise, in comparison with methods such as compressed sensing based detectors, minimum mean square error (MMSE), and zero forcing (ZF).

scholarly journals ISSOR Signal Detection for Energy Efficient and Low Complexity Large Scale MIMO System

2019 ◽  
Vol 9 (1S5) ◽  
pp. 327-334
Keyword(s):  
Signal Detection ◽  
Energy Efficient ◽  
Communication Systems ◽  
Large Scale ◽  
Mimo System ◽  
Low Complexity ◽  
High Energy ◽  
Base Station ◽  
User Equipment ◽  
Multiple User

Scalable version of multiuser MIMO called Large-scale MIMO is a one of the powerful technology in future wireless communication systems in which huge amount of BS (base station) antennas utilized to process multiple user equipment. Energy consumed is high with more antennas and also it leads to increase the signal detection complexity and overall circuit power consumption. Designing energy efficient and low complexity MIMO system is considered as a challenging issue. This paper presents the ISSOR signal detection for energy efficient and low complexity large scale MIMO system. VA-GSM (Variable Antenna Generalized spatial modulation) is used in which the number of active antenna transmissions are varied for every transmission in the large scale MIMO. In transmitter side, Eigen value based approach is used for antenna selection. Then, improved symmetric successive over relaxation (ISSOR) approach is proposed for low complexity signal detection in receiver side. The number of user equipment, transmit power, as well as the amount of antennas at the base station, are considered as the optimal system parameters which are chosen for enhancing the efficiency of utilized energy in the system. The proposed scheme implemented in MATLAB software. The proposed scheme attained the high energy efficiency compared to other approaches. Moreover, the BER is utilized to estimate the performance of an offered algorithm and also compared to the previously determined algorithm of existing literatures.

scholarly journals Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1564
Author(s):  
Hebiao Wu ◽  
Bin Shen ◽  
Shufeng Zhao ◽  
Peng Gong
Keyword(s):  
Signal Detection ◽  
Output Signal ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Base Station ◽  
Matrix Inversion ◽  
Iteration Algorithm

For multi-user uplink massive multiple input multiple output (MIMO) systems, minimum mean square error (MMSE) criterion-based linear signal detection algorithm achieves nearly optimal performance, on condition that the number of antennas at the base station is asymptotically large. However, it involves prohibitively high complexity in matrix inversion when the number of users is getting large. A low-complexity soft-output signal detection algorithm based on improved Kaczmarz method is proposed in this paper, which circumvents the matrix inversion operation and thus reduces the complexity by an order of magnitude. Meanwhile, an optimal relaxation parameter is introduced to further accelerate the convergence speed of the proposed algorithm and two approximate methods of calculating the log-likelihood ratios (LLRs) for channel decoding are obtained as well. Analysis and simulations verify that the proposed algorithm outperforms various typical low-complexity signal detection algorithms. The proposed algorithm converges rapidly and achieves its performance quite close to that of the MMSE algorithm with only a small number of iterations.

scholarly journals Design, Simulation & Concept Verification of 4 × 4, 8 × 8 MIMO With ZF, MMSE and BF Detection Schemes

2017 ◽  
Vol 13 (1) ◽  
pp. 69-74
Author(s):  
Arun Kumar ◽  
Piyush Vardhan
Keyword(s):  
Signal Detection ◽  
Communication Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Base Station ◽  
Wireless Communication Systems ◽  
Detection Techniques ◽  
Low Snr ◽  
Detection Schemes ◽  
Suitable Technique

Abstract A conventional MIMO system is designed consisting of 4 antenna elements at both the receiver and transmitter ends. Different kinds of signal detection techniques, namely, zero forcing (ZF), minimum mean square error (MMSE) and beamforming (BF), are used at the receiver end for signal detection. The performance of the system is analyzed by calculating BER vs SNR for each of the above techniques separately. The present work has been thoroughly analyzed and implemented using MATLAB. On the basis of the results obtained, it is summarized that as the values of SNR increase, BER decreases for ZF and MMSE and it almost vanishes to zero even for low SNR values if BF is used. Although ZF and MMSE are suitable for designing a conventional MIMO system with 4 antenna elements, it becomes too difficult for a large number of antenna elements due to its complexity of calculating the inverse of a (N × N) matrix. Based on the results analyzed so far, it is concluded that beamforming (BF) is a suitable technique for designing a system that has a large number of antenna elements at the base station. A further improved system with enhanced performance regarding lower BER for even smaller values of SNR is designed in the present study, consisting of 8 antennas at the base station. The results obtained are enthusiasm-provoking and encouraging for further studies to develop a concept for next-generation wireless communication systems with an optimum design.

scholarly journals A Survey on Spatial Modulation and MIMO System for Emerging Wireless Communication

2021 ◽  
Vol 9 (VI) ◽  
pp. 3059-3062
Author(s):  
Prabha Kumari
Keyword(s):  
Wireless Communication ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
High Energy ◽  
Spatial Modulation ◽  
Bandwidth Efficiency ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Rf Chain

In this paper we have studied about Spatial Modulation (SM) in MIMO system. Spatial modulation is a unique and newly proposed technique. Spatial modulation is a multiple input multiple output technique which provides higher throughput and gain as compared to Quadrature Amplitude Modulation. Spatial modulation is a technique which enhances the performance of MIMO system. Spatial modulation and MIMO technique are used to attracted research for its high energy and spectral efficiency because it is working on single RF chain. This paper has considered the advantages of spatial modulation and MIMO systems, using different technique to improve the bandwidth efficiency. Some of such MIMO systems applications are discussed wherein become a requirement for an emerging wireless communication system.

scholarly journals Maximizing Energy Efficiency for Consumption Circuit Power in Downlink Massive MIMO Wireless Networks

2017 ◽  
Vol 7 (6) ◽  
pp. 2977 ◽  
Author(s):  
Adeeb Salh ◽  
Lukman Audah ◽  
Nor Shahida M. Shah ◽  
Shipun A. Hamzah
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Data Rate ◽  
Optimal Number ◽  
Zero Forcing ◽  
High Data ◽  
Circuit Power

<span>Massive multi-input–multi-output (MIMO) systems are crucial to maximizing energy efficiency (EE) and battery-saving technology. Achieving EE without sacrificing the quality of service (QoS) is increasingly important for mobile devices. We first derive the data rate through zero forcing (ZF) and three linear precodings: maximum ratio transmission (MRT), zero forcing (ZF), and minimum mean square error (MMSE). Performance EE can be achieved when all available antennas are used and when taking account of the consumption circuit power ignored because of high transmit power. The aim of this work is to demonstrate how to obtain maximum EE while minimizing power consumed, which achieves a high data rate by deriving the optimal number of antennas in the downlink massive MIMO system. This system includes not only the transmitted power but also the fundamental operation circuit power at the transmitter signal. Maximized EE depends on the optimal number of antennas and determines the number of active users that should be scheduled in each cell. We conclude that the linear precoding technique MMSE achieves the maximum EE more than ZF and MRT</span><em></em><span>because the MMSE is able to make the massive MIMO system less sensitive to SNR at an increased number of antennas</span><span>.</span>

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 Near Optimal Receive Antenna Selection Scheme for MIMO System under Spatially Correlated Channel

2018 ◽  
Vol 8 (5) ◽  
pp. 3732
Author(s):  
Patel Sagar ◽  
Bhalani Jaymin
Keyword(s):  
Communication Systems ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Symbol Error Rate ◽  
Selection Scheme ◽  
Spatially Correlated ◽  
Spatially Correlated Channel ◽  
Correlated Channel ◽  
Receive Antenna

Spatial correlation is a critical impairment for practical Multiple Input Multiple Output (MIMO) wireless communication systems. To overcome from this issue, one of the solutions is receive antenna selection. Receive antenna selection is a low-cost, low-complexity and no requirement of feedback bit alternative option to capture many of the advantages of MIMO systems. In this paper, symbol error rate (SER) versus signal to noise ratio (SNR) performance comparasion of proposed receive antenna selection scheme for full rate non-orthogonal Space Time Block Code (STBC) is obtained using simulations in MIMO systems under spatially correlated channel at transmit and receive antenna compare with several existing receive antenna selection schemes. The performance of proposed receive antenna selection scheme is same as conventional scheme and beat all other existing schemes.

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