scholarly journals Joint Design of Massive MIMO Precoder and Security Scheme for Multiuser Scenarios under Reciprocal Channel Conditions

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Gustavo Anjos ◽  
Daniel Castanheira ◽  
Adão Silva ◽  
Atílio Gameiro ◽  
Marco Gomes ◽  
...  
Keyword(s):  
Channel Capacity ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Wireless Channel ◽  
Joint Design ◽  
Security Scheme ◽  
Working Principle ◽  
Transmitted Signal ◽  
Intended Receiver

The exploration of the physical layer characteristics of the wireless channel is currently the object of intensive research in order to develop advanced secrecy schemes that can protect information against eavesdropping attacks. Following this line of work, in this manuscript we consider a massive MIMO system and jointly design the channel precoder and security scheme. By doing that we ensure that the precoding operation does not reduce the degree of secrecy provided by the security scheme. The fundamental working principle of the proposed technique is to apply selective random rotations in the transmitted signal at the antenna level in order to achieve a compromise between legitimate and eavesdropper channel capacities. These rotations use the phase of the reciprocal wireless channel as a common random source between the transmitter and the intended receiver. To assess the security performance, the proposed joint scheme is compared with a recently proposed approach for massive MIMO systems. The results show that, with the proposed joint design, the number of antenna elements does not influence the eavesdropper channel capacity, which is proved to be equal to zero, in contrast to previous approaches.

scholarly journals Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 301
Author(s):  
Samarendra Nath Sur ◽  
Rabindranath Bera ◽  
Akash Kumar Bhoi ◽  
Mahaboob Shaik ◽  
Gonçalo Marques
Keyword(s):  
Channel Capacity ◽  
Massive Mimo ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Mimo System ◽  
Correlation Effect ◽  
Performance Comparison ◽  
Lattice Reduction ◽  
Detection Algorithms ◽  
Minimum Mean Squared Error

Massive multi-input-multi-output (MIMO) systems are the future of the communication system. The proper design of the MIMO system needs an appropriate choice of detection algorithms. At the same time, Lattice reduction (LR)-aided equalizers have been well investigated for MIMO systems. Many studies have been carried out over the Korkine–Zolotareff (KZ) and Lenstra–Lenstra–Lovász (LLL) algorithms. This paper presents an analysis of the channel capacity of the massive MIMO system. The mathematical calculations included in this paper correspond to the channel correlation effect on the channel capacity. Besides, the achievable gain over the linear receiver is also highlighted. In this study, all the calculations were further verified through the simulated results. The simulated results show the performance comparison between zero forcing (ZF), minimum mean squared error (MMSE), integer forcing (IF) receivers with log-likelihood ratio (LLR)-ZF, LLR-MMSE, KZ-ZF, and KZ-MMSE. The main objective of this work is to show that, when a lattice reduction algorithm is combined with the convention linear MIMO receiver, it improves the capacity tremendously. The same is proven here, as the KZ-MMSE receiver outperforms its counterparts in a significant margin.

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 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 Statistical Beamforming for Massive MIMO Systems with Distinct Spatial Correlations

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6255
Author(s):  
Taehyoung Kim ◽  
Sangjoon Park
Keyword(s):  
Massive Mimo ◽  
Degrees Of Freedom ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
High Signal ◽  
Spatial Correlations ◽  
Channel Correlation ◽  
Low Correlation ◽  
Noise Ratio

In this paper, we propose a novel statistical beamforming (SBF) method called the partial-nulling-based SBF (PN-SBF) to serve a number of users that are undergoing distinct degrees of spatial channel correlations in massive multiple-input multiple-output (MIMO) systems. We consider a massive MIMO system with two user groups. The first group experiences a low spatial channel correlation, whereas the second group has a high spatial channel correlation, which can happen in massive MIMO systems that are based on fifth-generation networks. By analyzing the statistical signal-to-interference-plus-noise ratio, it can be observed that the statistical beamforming vector for the low-correlation group should be designed as the orthogonal complement for the space spanned by the aggregated channel covariance matrices of the high-correlation group. Meanwhile, the spatial degrees of freedom for the high-correlation group should be preserved without cancelling the interference to the low-correlation group. Accordingly, a group-common pre-beamforming matrix is applied to the low-correlation group to cancel the interference to the high-correlation group. In addition, to deal with the intra-group interference in each group, the post-beamforming vector for each group is designed in the manner of maximizing the signal-to-leakage-and-noise ratio, which yields additional performance improvements for the PN-SBF. The simulation results verify that the proposed PN-SBF outperforms the conventional SBF schemes in terms of the ergodic sum rate for the massive MIMO systems with distinct spatial correlations, without the rate ceiling effect in the high signal-to-noise ratio region unlike conventional SBF schemes.

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 On the MIMO Capacity for Distributed System under Composite Rayleigh/Rician Fading and Shadowing

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Santiago González-Aurioles ◽  
J. L. Padilla ◽  
P. Padilla ◽  
Juan F. Valenzuela-Valdés ◽  
Juan C. Gonzalez-Macias
Keyword(s):  
Channel Capacity ◽  
Massive Mimo ◽  
Rayleigh Fading ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Rician Fading ◽  
Short Term ◽  
Multiple Input ◽  
Fading And Shadowing ◽  
The One

Wireless channels are commonly affected by short-term fading and long-term fading (shadowing). The shadowing effects must be taken into account also when mobility is present in the wireless scenario. Using a composite fading model, the total channel capacity can be studied for a scenario with short-term Rayleigh fading along with shadowing. This work provides quantitative results for these kinds of scenarios with Rayleigh fading and shadowing, considering also multiple-input and multiple-output systems, which have not been previously reported. In addition, the channel capacity has been studied in depth in its relation with the shadowing level, signal to noise ratio, and the number of elements in the multiple-input and multiple-output system. Moreover, the channel performance with shadowing has been compared to the one without it. Furthermore, Rician model with shadowing is studied and its results are reported. In addition, correlated and experimental results are provided. It is identified that the distributed MIMO systems can benefit from shadowing in Rician channels. This advantage has not been reported previously. This type of fading is proposed for massive MIMO by others and our results open the door to emulate massive MIMO on a reverberation chamber.

scholarly journals Analysis between Various Random MIMO systems Model On the Basis of Channel Capacity

2016 ◽  
Author(s):  
Shree Krishna Acharya
Keyword(s):  
Wireless Communication ◽  
Outage Probability ◽  
Channel Capacity ◽  
Mimo Systems ◽  
Mimo System ◽  
System Model ◽  
Mimo Channel ◽  
Systems Model ◽  
Capacity Model ◽  
Mimo Channel Capacity

Finding a good MIMO system model also major issue in Wireless Communication system. It is facing with so many problem, one of the major problem is finding good system model in terms of capacity. In this paper, we analyze the channel capacity of various MIMO system model with some constant SNR level and outage probability. We establish a novel idea for MIMO system models as consider as 2N- MIMO system model with constant SNR and outage probability. The channel capacity ratio is presented here on the basis of 2N- MIMO channel capacity model. Analysis of various MIMO system model show that it is better to use NT×NR MIMO system model then two NT/2×NR/2 MIMO system model in terms of channel capacity but it is not good for higher value of NT×NR

scholarly journals Channel Estimation for Frequency Division Duplexing Multi-user Massive MIMO Systems via Tensor Compressive Sensing

2017 ◽  
Vol 67 (6) ◽  
pp. 668
Author(s):  
Qingzhu Wang ◽  
Mengying Wei ◽  
Yihai Zhu
Keyword(s):  
Channel Estimation ◽  
Compressive Sensing ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Three Dimensional ◽  
Data Representation ◽  
Frequency Division ◽  
Frequency Division Duplexing

<p class="p1">To make full use of space multiplexing gains for the multi-user massive multiple-input multiple-output, accurate channel state information at the transmitter (CSIT) is required. However, the large number of users and antennas make CSIT a higher-order data representation. Tensor-based compressive sensing (TCS) is a promising method that is suitable for high-dimensional data processing; it can reduce training pilot and feedback overhead during channel estimation. In this paper, we consider the channel estimation in frequency division duplexing (FDD) multi-user massive MIMO system. A novel estimation framework for three dimensional CSIT is presented, in which the modes include the number of transmitting antennas, receiving antennas, and users. The TCS technique is employed to complete the reconstruction of three dimensional CSIT. The simulation results are given to demonstrate that the proposed estimation approach outperforms existing algorithms.</p>

scholarly journals Modified Conjugate Gradient Algorithms for Gram Matrix Inversion of Massive MIMO Downlink Linear Precoding

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2834-2840
Keyword(s):  
Conjugate Gradient ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Low Complexity ◽  
Matrix Inversion ◽  
Gram Matrix ◽  
Linear Precoding ◽  
Inversion Algorithm ◽  
The Matrix

This paper deals with various low complexity algorithms for higher order matrix inversion involved in massive MIMO system precoder design. The performance of massive MIMO systems is optimized by the process of precoding which is divided into linear and nonlinear. Nonlinear precoding techniques are most complex precoding techniques irrespective of its performance. Hence, linear precoding is generally preferred in which the complexity is mainly contributed by matrix inversion algorithm. To solve this issue, Krylov subspace algorithm such as Conjugate Gradient (CG) was considered to be the best choice of replacement for exact matrix inversions. But CG enforces a condition that the matrix needs to be Symmetric Positive Definite (SPD). If the matrix to be inverted is asymmetric then CG fails to converge. Hence in this paper, a novel approach for the low complexity inversion of asymmetric matrices is proposed by applying two different versions of CG algorithms- Conjugate Gradient Squared (CGS) and Bi-conjugate Gradient (Bi-CG). The convergence behavior and BER performance of these two algorithms are compared with the existing CG algorithm. The results show that these two algorithms outperform CG in terms of convergence speed and relative residue.

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.

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