Performance Analysis of 3D Massive MIMO Cellular Systems with Collaborative Base Station

Massive MIMO have drawn considerable attention as they enable significant capacity and coverage improvement in wireless cellular network. However, pilot contamination is a great challenge in massive MIMO systems. Under this circumstance, cooperation and three-dimensional (3D) MIMO are emerging technologies to eliminate the pilot contamination and to enhance the performance relative to the traditional interference-limited implementations. Motivated by this, we investigate the achievable sum rate performance of MIMO systems in the uplink employing cooperative base station (BS) and 3D MIMO systems. In our model, we consider the effects of both large-scale and small-scale fading, as well as the spatial correlation and indoor-to-outdoor high-rise propagation environment. In particular, we investigate the cooperative communication model based on 3D MIMO and propose a closed-form lower bound on the sum rate. Utilizing this bound, we pursue a “large-system” analysis and provide the asymptotic expression when the number of antennas at the BS grows large, and when the numbers of antennas at transceiver grow large with a fixed ratio. We demonstrate that the lower bound is very tight and becomes exact in the massive MIMO system limits. Finally, under the sum rate maximization condition, we derive the optimal number of UTs to be served.

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

Entropy ◽

10.3390/e21060573 ◽

2019 ◽

Vol 21 (6) ◽

pp. 573 ◽

Cited By ~ 3

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.

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Spatio-Radio Resource Management and Hybrid Beamforming for Limited Feedback Massive MIMO Systems

Electronics ◽

10.3390/electronics8101061 ◽

2019 ◽

Vol 8 (10) ◽

pp. 1061 ◽

Cited By ~ 3

Author(s):

Hedi Khammari ◽

Irfan Ahmed ◽

Ghulam Bhatti ◽

Masoud Alajmi

Keyword(s):

Massive Mimo ◽

Fourier Transforms ◽

Mimo Systems ◽

Limited Feedback ◽

Base Station ◽

Discrete Fourier Transforms ◽

Beam Selection ◽

Sum Rate ◽

Hybrid Beamforming ◽

Csi Feedback

In this paper, a joint spatio–radio frequency resource allocation and hybrid beamforming scheme for the massive multiple-input multiple-output (MIMO) systems is proposed. We consider limited feedback two-stage hybrid beamformimg for decomposing the precoding matrix at the base-station. To reduce the channel state information (CSI) feedback of massive MIMO, we utilize the channel covariance-based RF precoding and beam selection. This beam selection process minimizes the inter-group interference. The regularized block diagonalization can mitigate the inter-group interference, but requires substantial overhead feedback. We use channel covariance-based eigenmodes and discrete Fourier transforms (DFT) to reduce the feedback overhead and design a simplified analog precoder. The columns of the analog beamforming matrix are selected based on the users’ grouping performed by the K-mean unsupervised machine learning algorithm. The digital precoder is designed with joint optimization of intra-group user utility function. It has been shown that more than 50 % feedback overhead is reduced by the eigenmodes-based analog precoder design. The joint beams, users scheduling and limited feedbacK-based hybrid precoding increases the sum-rate by 27 . 6 % compared to the sum-rate of one-group case, and reduce the feedback overhead by 62 . 5 % compared to the full CSI feedback.

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On the Distribution of an Effective Channel Estimator for Multi-Cell Massive MIMO

10.20944/preprints201908.0169.v1 ◽

2019 ◽

Author(s):

Felipe Augusto Pereira de Figueiredo ◽

Claudio Ferreira Dias ◽

Fabbryccio A. C. M. Cardoso ◽

Gustavo Fraidenraich

Keyword(s):

Massive Mimo ◽

Large Scale ◽

Mimo Systems ◽

Base Station ◽

Noise Power ◽

Pilot Contamination ◽

Channel Estimator ◽

Symmetric Complex ◽

Mmse Estimator ◽

Effective Channel

Accurate channel estimation is of utmost importance for massive MIMO systems to provide significant improvements in spectral and energy efficiency. In this work, we present a study on the distribution of a simple but yet effective and practical channel estimator for multi-cell massive MIMO systems suffering from pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without previous knowledge of the inter-cell large-scale channel coefficients and noise power, asymptotically approximating the performance of the linear MMSE estimator as the number of antennas increases. We prove that the distribution of the proposed channel estimator can be accurately approximated by the circularly-symmetric complex normal distribution, when the number of antennas, M, deployed at the base station is greater than 10.

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Mitigating the Interference Caused by Pilot Contamination in Multi-cell Massive Multiple Input Multiple Output Systems Using Low Density Parity Check Codes in Uplink Scenario

Traitement du signal ◽

10.18280/ts.370619 ◽

2020 ◽

Vol 37 (6) ◽

pp. 1061-1074

Author(s):

Lokesh Bhardwaj ◽

Ritesh Kumar Mishra

Keyword(s):

Mimo System ◽

Multiple Input Multiple Output ◽

Base Station ◽

Low Density ◽

Pilot Contamination ◽

Parity Check ◽

Low Density Parity Check ◽

Multiple Input ◽

Input Multiple Output ◽

Sum Rate

The effects of pilot contamination (PC) on the performance of multi-cell multi-user massive multiple input multiple output (MC-MU-m-MIMO) system in uplink has been analyzed in this article. In a multi-cell scenario, the channel estimation (CE) at the desired cell using pilot reuse to avoid significant overhead results in poor CE due to PC. The improvement in degraded performance due to the effect of PC has been shown using low Density Parity Check (LDPC) codes. The comparative analysis of performance in terms of variation in bit error rate (BER) with the signal to noise ratio (SNR) for LDPC coded and uncoded information blocks of users has been shown when the number of cells sharing the same frequency band is varied. Further, the expression for sum-rate has been derived and its variation with the number of base station (BS) antennas has also been shown. The simulated results have shown that the LDPC coded scheme performs better than the uncoded counterpart and the sum-rate capacity increases when the strength of channel coefficients between the BS antennas of the desired cell and the users of remaining cells is less.

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Pilot Decontamination Using Asynchronous Fractional Pilot Scheduling in Massive MIMO Systems

Sensors ◽

10.3390/s20216213 ◽

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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On the Capacity and Transmission Techniques of Massive MIMO Systems

Wireless Communications and Mobile Computing ◽

10.1155/2018/9363515 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

Mohamed Abdul Haleem

Keyword(s):

Massive Mimo ◽

Mimo Systems ◽

Transmission Rate ◽

Mimo System ◽

Coupling Factor ◽

Base Station ◽

Power Sharing ◽

System Capacity ◽

Bit Rate ◽

Channel Coupling

A massive MIMO wireless system is a multiuser MISO system where base stations consist of a large number of antennas with respect to number of user devices, each equipped with a single antenna. Massive MIMO is seen as the way forward in enhancing the transmission rate and user capacity in 5G wireless. The potential of massive MIMO system lies in the ability to almost always realize multiuser channels with near zero mutual coupling. Coupling factor reduces by 1/2 for each doubling of transmit antennas. In a high bit rate massive MIMO system with m base station antennas and n users, downlink capacity increases as log2⁡m bps/Hz, and the capacity per user reduces as log2⁡n bps/Hz. This capacity can be achieved by power sharing and using signal weighting vectors aligned to respective 1×m channels of the users. For low bit rate transmission, time sharing achieves the capacity as much as power sharing does. System capacity reduces as channel coupling factor increases. Interference avoidance or minimization strategies can be used to achieve the available capacity in such scenarios. Probability distribution of channel coupling factor is a convenient tool to predict the number of antennas needed to qualify a system as massive MIMO.

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Angular Domain Data-Assisted Channel Estimation for Pilot Decontamination in Massive MIMO

Mobile Information Systems ◽

10.1155/2017/2785948 ◽

2017 ◽

Vol 2017 ◽

pp. 1-9

Author(s):

Yihenew Beyene ◽

Kalle Ruttik ◽

Riku Jäntti

Keyword(s):

Channel Estimation ◽

Antenna Arrays ◽

Mean Squared Error ◽

Mimo Systems ◽

Mimo System ◽

Base Station ◽

Pilot Contamination ◽

Angular Domain ◽

Matrix Estimation ◽

Minimum Mean Squared Error

Massive Multiple-Input-Multiple-Output (M-MIMO) system is a promising technology that offers to mobile networks substantial increase in throughput. In Time-Division Duplexing (TDD), the uplink training allows a Base Station (BS) to acquire Channel State Information (CSI) for both uplink reception and downlink transmission. This is essential for M-MIMO systems where downlink training pilots would consume large portion of the bandwidth. In densely populated areas, pilot symbols are reused among neighboring cells. Pilot contamination is the fundamental bottleneck on the performance of M-MIMO systems. Pilot contamination effect in antenna arrays can be mitigated by treating the channel estimation problem in angular domain where channel sparsity can be exploited. In this paper, we introduce a codebook that projects the channel into orthogonal beams and apply Minimum Mean-Squared Error (MMSE) criterion to estimate the channel. We also propose data-aided channel covariance matrix estimation algorithm for angular domain MMSE channel estimator by exploiting properties of linear antenna array. The algorithm is based on simple linear operations and no matrix inversion is involved. Numerical results show that the algorithm performs well in mitigating pilot contamination where the desired channel and other interfering channels span overlapping angle-of-arrivals.

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Evaluation of different quantization resolution levels on the BER performance of massive MIMO systems under different operating scenarios

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v23.i3.pp1493-1500 ◽

2021 ◽

Vol 23 (3) ◽

pp. 1493

Author(s):

Hayder Khaleel AL-Qaysi ◽

Tahreer Mahmood ◽

Khalid Awaad Humood

Keyword(s):

Massive Mimo ◽

Large Scale ◽

Influence Factor ◽

Mimo Systems ◽

Mimo System ◽

Base Station ◽

Analog To Digital ◽

Simulation Performance ◽

Hardware Costs ◽

Ber Performance

The massive MIMO system is one of the main technologies in the fifth generation (5G) of telecommunication systems, also recognized as a highly large-scale system. Constantly in massive MIMO systems, the base station (BS) is provided with a large number of antennas, and this large number of antennas need high-quantization resolution levels analog-to-digital converters (ADCs). In this situation, there will be more power consumption and hardware costs. This paper presents the simulation performance of a suggested method to investigate and analyze the effects of different quantization resolution levels of ADCs on the bit error rate (BER) performance of massive MIMO system under different operating scenarios using MATLAB software. The results show that the SNR exceeds 12 dB accounts for only 0.001% of BER signals when the number of antennas 60 with low quantization a 2 bits’ levels ADCs, approximately. But when the antenna number rises to 300, the SNR exceeds 12 dB accounts for almost 0.01% of BER transmitted signals. Comparably with the BER performance of high quantization, 4 bits-quantization resolution levels ADCs with the same different antennas have a slight degradation. Therefore, the number of antennas is a very important influence factor.

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Time-shifted Pilot-based Scheduling with Adaptive Optimization for Pilot Contamination Reduction in Massive MIMO

Journal of Telecommunications and Information Technology ◽

10.26636/jtit.2020.145020 ◽

2020 ◽

Vol 4 ◽

pp. 10-21

Author(s):

Ambala Pradeep Kumar ◽

Tadisetty Srinivasulu

Keyword(s):

Massive Mimo ◽

Communication Systems ◽

Large Scale ◽

Mimo System ◽

Base Station ◽

Superior Performance ◽

Optimal Time ◽

Pilot Contamination ◽

Adaptive Optimization ◽

User Grouping

Massive multiple-input multiple-output (MIMO) is considered to be an emerging technique in wireless communication systems, as it offers the ability to boost channel capacity and spectral efficiency. However, a massive MIMO system requires huge base station (BS) antennas to handle users and suffers from inter-cell interference that leads to pilot contamination. To cope with this, time-shifted pilots are devised for avoiding interference between cells, by rearranging the order of transmitting pilots in different cells. In this paper, an adaptive-elephant-based spider monkey optimization (adaptive ESMO) mechanism is employed for time-shifted optimal pilot scheduling in a massive MIMO system. Here, user grouping is performed with the sparse fuzzy c-means (Sparse FCM) algorithm, grouping users based on such parameters as large-scale fading factor, SINR, and user distance. Here, the user grouping approach prevents inappropriate grouping of users, thus enabling effective grouping, even under the worst conditions in which the channel operates. Finally, optimal time-shifted scheduling of the pilot is performed using the proposed adaptive ESMO concept designed by incorporating adaptive tuning parameters. The efficiency of the adaptive ESMO approach is evaluated and reveals superior performance with the highest achievable uplink rate of 43.084 bps/Hz, the highest SINR of 132.9 dB, and maximum throughput of 2.633 Mbps

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Mitigating Pilot Contamination with Scrambling Sequences

10.20944/preprints201906.0247.v1 ◽

2019 ◽

Author(s):

Felipe Augusto Pereira de Figueiredo

Keyword(s):

Massive Mimo ◽

Mimo Systems ◽

Base Station ◽

Frequency Reuse ◽

Pilot Contamination ◽

Orthogonality Property ◽

Frequency Reuse Factor

In this letter, we advocate that it is possible to mitigate Pilot Contamination in Massive MIMO systems by scrambling the pilot sequences with a Base Station (BS) scrambling sequence. It is possible if a set of sequences is carefully designed to meet the orthogonality property defined in this letter. Each BS possesses its own scrambling sequence that can be reused the same way frequency reuse is applied to cell deployment. The main advantage of the prosed pilot generation scheme is that the frequency reuse factor can be set to 1, the most aggressive one, while the scrambling sequences can be reused with much less aggressive reuse factors (e.g. 4, 7, 9, 12, etc.), which in consequence results in pilot contamination mitigation and increased system's performance.

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