A practical approach to improve product of energy efficiency and capacity rate in MU-MIMO systems

2020 ◽  
Vol 16 (2) ◽  
pp. 183-202
Author(s):  
Ashu Taneja ◽  
Nitin Saluja
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Communication Systems ◽  
Mimo Systems ◽  
Mimo System ◽  
Practical Approach ◽  
System Capacity ◽  
Content Type ◽  
Channel Interference ◽  
Sum Rate

Purpose The major challenges in the modern-day wireless communication systems are increased co-channel interference owing to large number of users and the increased energy consumption owing to high circuit and/or hardware power consumption. Hence, the purpose of this paper is to present a practical approach involving linear precoding, channel estimation, user selection (US) and transmit antenna selection (AS) for enhanced reliability in multiuser multiple-input multiple output (MU-MIMO) system. Design/methodology/approach The proposed technique considers systematic and optimum deployment of users and transmits antennas for each selected user which enhances the sum rate or the system capacity. The comparison of algorithms, namely, norm-based and capacity-based US is presented with its implementation with precoding techniques, namely, block-diagonalization (BD) and zero-forcing with combining (ZFC) which is used to minimize co-channel interference. In this paper, a power consumption model is proposed for energy efficiency calculation in MU-MIMO system. Also, post analysis, the variant of US and AS algorithms optimizing the performance of BD and ZFC precoding technique is proposed. Findings It is seen that the proposed MU-MIMO system with norm-based US and norm-based AS improves over existing US-based systems by 43% in terms of sum rate and 19% in terms of energy efficiency for 100 users. Originality/value It is seen that the proposed MU-MIMO system with norm-based US and norm-based AS improves over existing US-based systems by 43% in terms of sum rate and 19% in terms of energy efficiency for 100 users.

scholarly journals Energy Efficiency Augmentation in Massive MIMO Systems through Linear Precoding Schemes and Power Consumption Modeling

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Rao Muhammad Asif ◽  
Jehangir Arshad ◽  
Mustafa Shakir ◽  
Sohail M. Noman ◽  
Ateeq Ur Rehman
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Antenna Arrays ◽  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Mimo System ◽  
Base Station ◽  
Total Power ◽  
Minimum Mean Squared Error

Massive multiple-input multiple-output or massive MIMO system has great potential for 5th generation (5G) wireless communication systems as it is capable of providing game-changing enhancements in area throughput and energy efficiency (EE). This work proposes a realistic and practically implementable EE model for massive MIMO systems while a general and canonical system model is used for single-cell scenario. Linear processing schemes are used for detection and precoding, i.e., minimum mean squared error (MMSE), zero-forcing (ZF), and maximum ratio transmission (MRT/MRC). Moreover, a power dissipation model is proposed that considers overall power consumption in uplink and downlink communications. The proposed model includes the total power consumed by power amplifier and circuit components at the base station (BS) and single antenna user equipment (UE). An optimal number of BS antennas to serve total UEs and the overall transmitted power are also computed. The simulation results confirm considerable improvements in the gain of area throughput and EE, and it also shows that the optimum area throughput and EE can be realized wherein a larger number of antenna arrays at BS are installed for serving a greater number of UEs.

Hybrid multibeam forming and multiuser detection technique for MU-MIMO system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
D. Lalitha Kumari ◽  
M.N. Giri Prasad
Keyword(s):  
Energy Efficiency ◽  
Error Rate ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Experimental Results ◽  
Rate Performance ◽  
Hardware Complexity ◽  
Content Type ◽  
Simulation Results

PurposeIn recent years, multiuser-multiple-input multiple-output (MU-MIMO)-based wireless communication system has emerged as a prominent 5G technique that has several advantages over conventional MIMO systems such as high data rate and channel capacity. In this paper, the authors introduce a novel low-complexity radix factorization-based fast Fourier transform (FFT) as a multibeamformer and maximal likelihood-MU detection (ML-MUD) techniques as an optimal signal subdetector which results with considerable complexity reduction with intolerable error rate performance.Design/methodology/approachThe proposed radix-factorized FFT-multibeamforming (RF-FFT-MBF) architectures have the potential to reduce both hardware complexity and energy consumptions as compared to its state-of-the-art methods while meeting the throughput requirements of emerging 5G devices. Here through simulation results, the efficiency of the scaled ML subdetector system is compared with the conventional ML detectors.FindingsHere through simulation results, the efficiency of the scaled ML subdetector system is compared with the conventional ML detectors. Through experimental results, it is well proved that the proposed detector offers significant hardware and energy efficiency with the least possible error rate performance overhead.Originality/valueHere through simulation results, the efficiency of the scaled ML subdetector system is compared with the conventional ML detectors. Through experimental results, it is well proved that the proposed detector offers significant hardware and energy efficiency with the least possible error rate performance overhead.

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 Advanced Hybrid Beamforming Technique in MU-MIMO Systems

2020 ◽  
Vol 10 (17) ◽  
pp. 5961
Author(s):  
Seong-Joon Shim ◽  
Seulgi Lee ◽  
Won-Seok Lee ◽  
Jae-Hyun Ro ◽  
Jung-In Baik ◽  
...  
Keyword(s):  
Communication Technology ◽  
Communication Systems ◽  
High Performance ◽  
Mimo Systems ◽  
Error Performance ◽  
Fifth Generation ◽  
New Radio ◽  
Sum Rate ◽  
Hybrid Beamforming ◽  
Beam Patterns

This paper proposes a high performance wireless commmunication technology in MU-MIMO systems. The millimeter wave (mmWave) communication technology was considered for the future wireless communication systems such as the fifth-generation new radio (5G NR). In 5G NR, the mmWave communication technology was studied to increase the use of wide bandwidth and the data rate. Therefore, MU-MIMO systems can be used in mmWave. To decrease the complexity of conventional digital beamforming system, the hybrid beamforming system was studied. In particular, the proposed hybrid beamforming system improves the error performance and average sum rate in partially connected structure (PCS) hybrid beamforming system. The proposed PCS hybrid beamforming system forms variously combined beam patterns using the information of azimuth and elevation angles for the multi-paths according to the number of bits. In addition, the azimuth and elevation angles among the formed beam patterns are estimated according to the received signal strength (RSS). In the simulation results, the proposed PCS hybrid beamforming system has better error performance and the average sum rate than the conventional hybrid beamforming system.

scholarly journals Energy efficiency and sum rate tradeoffs for massive MIMO systems with underlaid device-to-device communications

2016 ◽  
Vol 2016 (1) ◽  
Author(s):  
Serveh Shalmashi ◽  
Emil Björnson ◽  
Marios Kountouris ◽  
Ki Won Sung ◽  
Mérouane Debbah
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Device To Device ◽  
Sum Rate

scholarly journals Adaptive Energy Efficiency Based Power Allocation for MIMO Radar Network

2019 ◽  
Vol 9 (1) ◽  
pp. 1720-1727
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Power Allocation ◽  
Target Detection ◽  
Communication Systems ◽  
Multiple Antennas ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Ratio Test ◽  
Input Multiple Output

Multiple-input multiple-output (MIMO) radar is used extensively due to its application of simultaneous transmission and reception of multiple signals through multiple antennas or channels. MIMO radar receives enormous attention in communication technologies due to its better target detection, higher resolution and improved accurate target parameter estimation. The MIMO radar has several antennas for transmitting the information and also the reflected signals from the target is received by the multiple antennas and it mainly used in military and civilian fields. But sometimes the performance of the MIMO radars is degraded due to its limited power. So the optimum power allocation is required in the communication systems of MIMO radar to improve its performance. In this paper, an Energy Efficiency based Power Allocation (EEPA) is used to allocate the power to a user of the clusters and also across the clusters. Here, the MIMO radars are clustered by using a naive bayes classifier. Subsequently, an efficient target detection is achieved by using Generalized Likelihood Ratio Test (GLRT) and then the clusters are divided into primary and distributive clusters based on the distance from the target. Here, the proposed methodology is named as EEPA-GLRT and the implementation of this MIMO radar system with an effective power allocation is done by Labview. The performance of the EEPA-GLRT methodology is analyzed in terms of the power consumption of various clusters. The performance of the EEPA-GLRT methodology is compared with Generalized Nash Game (GNG) method and it shows the power consumption of EEPA-GLRT is 0.0549 for cluster 1 of scenario 1, which is less when compared to the GNG method.

scholarly journals Sum-Rate of Multi-User MIMO Systems with Multi-Cell Pilot Contamination in Correlated Rayleigh Fading Channel

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 573 ◽  
Author(s):  
Menghan Wang ◽  
Dongming Wang
Keyword(s):  
Rayleigh Fading ◽  
Gaussian Approximation ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Moment Generating Function ◽  
Base Station ◽  
Pilot Contamination ◽  
Input Multiple Output ◽  
Sum Rate

This paper presents some exact results on the sum-rate of multi-user multiple-input multiple-output (MU-MIMO) systems subject to multi-cell pilot contamination under correlated Rayleigh fading. With multi-cell multi-user channel estimator, we give the lower bound of the sum-rate. We derive the moment generating function (MGF) of the sum-rate and then obtain the closed-form approximations of the mean and variance of the sum-rate. Then, with Gaussian approximation, we study the outage performance of the sum-rate. Furthermore, considering the number of antennas at base station becomes infinite, we investigate the asymptotic performance of the sum-rate. Theoretical results show that compared to MU-MIMO system with perfect channel estimation and no pilot contamination, the variance of the sum-rate of the considered system decreases very quickly as the number of antennas increases.

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).

Hybrid Multi Beam Forming and Multi User Detection Technique for MU MIMO System

2021 ◽  
Author(s):  
A. Mary joy Kinol ◽  
A Sahaya Anselin nisha ◽  
Marshiana D ◽  
Krishnamoorthy N.R
Keyword(s):  
Energy Efficiency ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Error Rate ◽  
Mimo Systems ◽  
Mimo System ◽  
Beam Forming ◽  
Rate Performance ◽  
Hardware Complexity ◽  
5G Systems

Abstract Multi user - Multiple-input multiple-output (MU-MIMO) based wireless communication system has several advantage over conventional MIMO systems such as high data rate and channel capacity which drawn great attention recently and prominently preferred for 5G systems. And on the other side interferences due to the multi user mobile environment such as co-channel interference and multiple access interference the overall system performance will be degraded and highly reliable techniques need to be incorporate to improve the Quality of services. Moreover the energy efficiency and compactness requirement of 5G systems presents new challenges to investigate techniques for reliable communications. In this paper we introduce a novel low-complexity radix factorization based fast Fourier transform multi beam former and maximal likelihood –multi user detection (ML-MUD) techniques as signal detector tailored with optimal sub detector systems which results with considerable complexity reduction with intolerable error rate performance. The proposed radix factorized Fast Fourier transform - multi-beam forming (RF-FFT-MBF) architectures have the potential to reduce both hardware complexity and energy consumptions as compared to its state-of-the-art methods while meeting the throughput requirements of emerging 5G devices. Here through simulation results the efficiency of scaled ML sub detector system at the downlink side is compared with the conventional ML detectors. Through experimental results it is well proved that the proposed detector offers significant hardware and energy efficiency with least possible error rate performance overhead.

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