Base Station Density Bounded by Maximum Outage Probability in Massive MIMO System

2015 ◽  
Author(s):  
Xun Zou ◽  
Gaofeng Cui ◽  
Minghuan Tang ◽  
Weidong Wang
Keyword(s):  
Outage Probability ◽  
Massive Mimo ◽  
Mimo System ◽  
Base Station ◽  
Station Density

A companding approach for PAPR suppression in OFDM based massive MIMO system

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ajay Kumar Yadav ◽  
Pritam Keshari Sahoo ◽  
Yogendra Kumar Prajapati
Keyword(s):  
Massive Mimo ◽  
Orthogonal Frequency Division Multiplexing ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Average Power ◽  
Base Station ◽  
Convex Optimization Problem ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm

Abstract Orthogonal frequency division multiplexing (OFDM) based massive multiuser (MU) multiple input multiple output (MIMO) system is popularly known as high peak-to-average power ratio (PAPR) issue. The OFDM-based massive MIMO system exhibits large number of antennas at Base Station (BS) due to the use of large number of high-power amplifiers (HPA). High PAPR causes HPAs to work in a nonlinear region, and hardware cost of nonlinear HPAs are very high and also power inefficient. Hence, to tackle this problem, this manuscript suggests a novel scheme based on the joint MU precoding and PAPR minimization (PP) expressed as a convex optimization problem solved by steepest gradient descent (GD) with μ-law companding approach. Therefore, we develop a new scheme mentioned to as MU-PP-GDs with μ-law companding to minimize PAPR by compressing and enlarging of massive MIMO OFDM signals simultaneously. At CCDF = 10−3, the proposed scheme (MU-PP-GDs with μ-law companding for Iterations = 100) minimizes the PAPR to 3.70 dB which is better than that of MU-PP-GDs, (iteration = 100) as shown in simulation results.

scholarly journals Optimal Low-Power Design of a Multicell Multiuser Massive MIMO System at 3.7 GHz for 5G Wireless Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Michel Matalatala ◽  
Margot Deruyck ◽  
Emmeric Tanghe ◽  
Luc Martens ◽  
Wout Joseph
Keyword(s):  
Low Power ◽  
Communication Networks ◽  
Massive Mimo ◽  
Mimo System ◽  
Low Power Design ◽  
Base Station ◽  
Base Stations ◽  
Reference Network ◽  
Power Requirement ◽  
Time Frequency

Massive MIMO techniques are expected to deliver significant performance gains for the future wireless communication networks by improving the spectral and the energy efficiencies. In this paper, we propose a method to optimize the positions, the coverage, and the energy consumption of the massive MIMO base stations within a suburban area in Ghent, Belgium, while meeting the low power requirements. The results reveal that massive MIMO provides better performances for the crowded scenario where users’ mobility is limited. With 256 antennas, a massive MIMO base station can simultaneously multiplex 18 users at the same time-frequency resource while consuming 8 times less power and providing 200 times more capacity than a 4G reference network for the same coverage. Moreover, a pilot reuse pattern of 3 is recommended in a multiuser multicell environment to obtain a good tradeoff between the high spectral efficiency and the low power requirement.

Signal Detection Algorithms for Massive MIMO

2014 ◽  
Vol 1049-1050 ◽  
pp. 2063-2068
Author(s):  
Xiao Tian Wang ◽  
Long Xiang Yang
Keyword(s):  
Signal Detection ◽  
Massive Mimo ◽  
Large Scale ◽  
Mimo System ◽  
Base Station ◽  
Mobile Systems ◽  
Detection Algorithms ◽  
Fifth Generation ◽  
Base Station Antennas ◽  
Large Scale Antenna Systems

massive MIMO (also known as Large-Scale Antenna Systems),which is one of the key technologies for the fifth generation (5G) mobile systems, brings huge improvements in spectral efficiency and energy efficiency through the use of a large excess of antennas for base station. This paper analyses and simulates the performances of several signal detection algorithms under the massive MIMO system model. The results show that when the number of base station antennas is considerably larger than the number of users, even the simple signal detection algorithms can achieve good system performance.

scholarly journals On the Capacity and Transmission Techniques of Massive MIMO Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
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.

scholarly journals Secure Massive MIMO System with Two-Way Relay Cooperative Transmission in 6G Networks

2020 ◽  
Author(s):  
Yumeng Su ◽  
Hongyuan Gao ◽  
Shibo Zhang
Keyword(s):  
Massive Mimo ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Cooperative Transmission ◽  
Transmission Mode ◽  
Security Issue ◽  
Legitimate User ◽  
Input Multiple Output ◽  
Multiple Relay

Abstract With the advent of Internet of Everything (IoE) and the era of big data, massive multiple-input multiple-output (MIMO) is considered an essential technology to meet the growing communication requirements for beyond 5G and the forthcoming 6G networks. This paper considers a secure massive MIMO system, where the legitimate user and the base station (BS) exchange messages via two-way relays with the presence of passive eavesdroppers. To achieve the trade-off between the physical-layer security and communication reliability, we design a cooperative transmission mode based on multiple-relay collaboration, where some relays broadcast the received signals and other relays act as friendly jammers to prevent the interception by eavesdroppers. A quantum chemical reaction optimization (QCRO) algorithm is proposed to find the most suitable scheme for multiple-relay collaboration. Simulation results highlight excellent performance of the proposed transmission mode under QCRO in different communication scenarios, which can be considered a potential solution for the security issue in future wireless 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

Performance Evaluation of Precoding Schemes for Multi User Massive MIMO System Over Nakagami-m Fading Channel

2021 ◽  
Author(s):  
Sultan.F Feisso Meko ◽  
Muluneh Mekonnen Tulu ◽  
Terefe Bahiru Bashu
Keyword(s):  
Performance Evaluation ◽  
Wireless Communication ◽  
Antenna Arrays ◽  
Interference Cancellation ◽  
Fading Channel ◽  
Massive Mimo ◽  
Mimo System ◽  
Base Station ◽  
Communication Link ◽  
User Interference

Abstract Nowadays, wireless communication system plays great roles in our dailyactivities and different improvements are requiring because the number of users increase from time to time. At the same time, users need high throughput and link reliability. The forthcoming generation of wireless communication will have to deal with some core requirements for serving large number of users simultaneously, upholdinghigh throughput for each user, assuring less energy consumption, etc. Inter-user interference has a major impact when a wireless communication link has a large number of users. To maintain a particular desired quality of service, sophisticated transmission mechanisms such as interference cancellation need be implemented. As a result, MU-massive MIMO with extremely huge antenna arrays is recommended. The term ”MU-massive MIMO” refers to a system with hundreds or thousands of antennas servicing tens of thousands of customers.Inter-user interference was greatly decreased once the channel vectors were closely orthogonal. As a result, high data rates can be supplied to multiple users at the same time. In this work, researcher investigated performance evaluation of a MU-massive MIMO utilizing different precoding schemes (like, MMSE, ZF, MRT) over nakagami-m fading channel with CSI at base station and users’ terminal. In addition, the researcher analyzed the outcome of pilot reuse factors and shaping (m) parameter.

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.

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