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

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.

scholarly journals Performance Analysis of Large-Scale MU-MIMO With a Simple and Effective Chanel Estimator

2019 ◽  
Author(s):  
Felipe Augusto Pereira de Figueiredo ◽  
Claudio Ferreira Dias ◽  
Eduardo Rodrigues de Lima ◽  
Gustavo Fraidenraich
Keyword(s):  
Mean Square Error ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Noise Power ◽  
Mean Square ◽  
Pilot Contamination ◽  
Channel Estimator

Accurate channel estimation is of utmost importance for massive MIMO systems that allow providing significant improvements in spectral and energy efficiency. In this work, we investigate the spectral efficiency performance and present a channel estimator for multi-cell massive MIMO systems subjected to pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without prior knowledge of the inter-cell large-scale channel coefficients and noise power. The estimator approximates the performance of a linear Minimum Mean Square Error (MMSE) as the number of antennas increases. Following, we derive a lower bound closed-form spectral efficiency of the Maximum Ratio Combining (MRC) detector in the proposed channel estimator. The simulation results highlight that the proposed estimator performance approaches the linear minimum mean square error (LMMSE) channel estimator asymptotically.

scholarly journals On the Application of Massive MIMO Systems to Machine Type Communications

2018 ◽  
Author(s):  
Felipe A. P. de Figueiredo ◽  
Fabbryccio A. C. M. Cardoso ◽  
Ingrid Moerman ◽  
Gustavo Fraidenraichz
Keyword(s):  
Interference Cancellation ◽  
Massive Mimo ◽  
Large Scale ◽  
Mimo Systems ◽  
Detection Methods ◽  
Channel Estimator ◽  
Time Frequency ◽  
Machine Type ◽  
Machine Type Communications ◽  
Optimal Linear

This paper evaluates the feasibility of applying Massive MIMO to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), devised to exclusively consume data traffic from Machine Type Communications (MTC) devices, the capacity (i:e:, number of connected devices) of MTC networks and, in turn, that of the whole system, can be increased by clustering such devices and letting each cluster share the same time-frequency physical resource blocks. Following this research line, we study the possibility of employing sub-optimal linear detectors to the problem and present a simple and practical channel estimator that works without previous knowledge of the large-scale channel coefficients. Our simulation results suggest that the proposed channel estimator performs asymptotically as well as the MMSE estimator with respect to the number of antennas and the uplink transmission power. Furthermore, the results also indicate that, as the number of antennas is made progressively larger, the performance of sub-optimal linear detection methods approaches the perfect interference-cancellation bound. The findings presented in this paper shed light on and motivate for new and exciting research lines towards a better understanding of the use of massive MIMO in MTC networks.

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

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.

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

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

scholarly journals Mitigating Pilot Contamination with Scrambling Sequences

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.

User grouping and optimization-based pilot scheduling for mitigating the pilot contamination in massive multi cell MIMO systems

2020 ◽  
pp. 2050057
Author(s):  
Ambala Pradeep Kumar ◽  
Tadisetty Srinivasulu
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Large Scale ◽  
Mimo Systems ◽  
Spider Monkey ◽  
Achievable Rate ◽  
Pilot Contamination ◽  
User Grouping ◽  
Spider Monkey Optimization ◽  
The Impact

Massive multiple-input multiple-output (massive MIMO) is a promising approach in wireless communication systems for providing improved link reliability and spectral efficiency and it helps several users. The main aim is to solve pilot contamination issue in massive MIMO systems; this research paper utilizes two approaches for reducing the contamination. This paper presents the user grouping approach based on sparse fuzzy C-means clustering (sparse FCM), which groups user parameters based on parameters such as large-scale fading factor, SINR, and user distance. Here, same pilot sequences are assigned to center users in which the impact of pilot contamination is limited, while the algorithm assigns orthogonal pilot sequences to the edge users that suffer severely from pilot contamination. Therefore, the proposed user grouping keeps away from the inappropriate grouping of users, enabling effective grouping even under the worst situations of the channel. Secondly, pilot scheduling is done based on elephant spider monkey optimization (ESMO), which is designed by integrating elephant herding optimization (EHO) into spider monkey optimization (SMO). The performance of pilot scheduling based on grouping-based ESMO is evaluated based on achievable rate and SINR. The proposed method achieves maximal achievable rate of 41.29[Formula: see text]bps/Hz and maximal SINR of 124.31[Formula: see text]dB.

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

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Xingwang Li ◽  
Lihua Li ◽  
Ling Xie ◽  
Xin Su ◽  
Ping Zhang
Keyword(s):  
Lower Bound ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Base Station ◽  
Cellular Systems ◽  
Small Scale ◽  
Pilot Contamination ◽  
3D Mimo ◽  
Sum Rate

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.

scholarly journals Massive MIMO User Location Based Pilot Allocation in Massive MIMO Systems

2020 ◽  
Vol 9 (5) ◽  
pp. 204-210
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Polar Angle ◽  
Base Station ◽  
Polar Coordinate System ◽  
Pilot Contamination ◽  
Pilot Allocation ◽  
Polar Coordinate ◽  
Speed Simulation ◽  
User Location

Aiming at the problem of massive MIMO pilot contamination, a user location information based pilot allocation scheme is proposed. The proposed scheme sorts the users and assigns pilots in accordance to the polar angle of the user's location in the polar coordinate system with the base station of the cell as the pole. The scheme combines the characteristics of the directional large line, and by controlling the reuse distance of the pilots in a relatively long range, the goals of reducing pilot contamination is improving system reachability and speed. Simulation results show that the proposed scheme not only effectively reduce pilot contamination among users, but also improves the performance gap between different users with the improved system fairness

scholarly journals Semi-blind channel estimation based on Modified CMA and unitary scrambling for massive MIMO systems

2021 ◽  
Author(s):  
Noura Sellami ◽  
Mohamed Siala
Keyword(s):  
Channel Estimation ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Pilot Contamination ◽  
Constant Modulus Algorithm ◽  
Unitary Matrices ◽  
Channel Estimator ◽  
Blind Channel ◽  
Input Multiple Output

Abstract Pilot contamination is one of the main impairments in multi-cell massive Multiple-Input Multiple-Output (MIMO) systems. In order to improve the channel estimation in this context, we propose to use a semi-blind channel estimator based on the constant modulus algorithm (CMA). We consider an enhanced version of the CMA namely the Modified CMA (MCMA) which modifies the cost function of the CMA algorithm to the sum of cost functions for real and imaginary parts. Due to pilot contamination, the channel estimator may estimate the channel of a contaminating user instead of that of the user of interest (the user for which the Base Station wants to estimate the channel and then the data). To avoid this, we propose to scramble the users sequences before transmission. We consider different methods to perform unitary scrambling based on rotating the transmitted symbols (one Dimensional (1-D) scrambling) and using unitary matrices (two-Dimensional (2-D) scrambling). At the base station, the received sequence of the user of interest is descrambled leading to a better convergence of the channel estimator. We also consider the case where the Automatic Repeat reQuest (ARQ) protocol is used. In this case, using scrambling leads to a significant gain in terms of BLock Error Rate (BLER) due to the change of the contaminating users data from one transmission to another induced by scrambling.

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