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

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.

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 578
Author(s):  
Robin Chataut ◽  
Robert Akl ◽  
Utpal Kumar Dey ◽  
Mohammadreza Robaei

With the limitedness of the sub-6 GHz bandwidth, the world is exploring a thrilling wireless technology known as massive MIMO. This wireless access technology is swiftly becoming key for 5G, B5G, and 6G network deployment. The massive MIMO system brings together antennas at both base stations and the user terminals to provide high spectral service. Despite the fact that massive MIMO offers astronomical benefits such as low latency, high data rate, improved array gain, and far better reliability, it faces several implementation challenges due to the hundreds of antennas at the base station. The signal detection at the base station during the uplink is one of the critical issues in this technology. Detection of user signal becomes computationally complex with a multitude of antennas present in the massive MIMO systems. This paper proposes a novel preconditioned and accelerated Gauss–Siedel algorithm referred to as Symmetric Successive Over-relaxation Preconditioned Gauss-Seidel (SSORGS). The proposed algorithm will address the signal detection challenges associated with massive MIMO technology. Furthermore, we enhance the convergence rate of the proposed algorithm by introducing a novel Symmetric Successive Over-relaxation preconditioner (SSOR) scheme and an initialization scheme based on the instantaneous channel condition between the base station and the user. The simulation results show that the proposed algorithm referred to as Symmetric Successive Over-relaxation Preconditioned Gauss-Seidel (SSORGS) provides optimal BER performance. At BER =10−3, over the range of SNR, the SSORGS algorithm performs better than the traditional algorithms. Additionally, the proposed algorithm is computationally more efficient than the traditional algorithms. Furthermore, we designed a comprehensive hardware architecture for the SSORGS algorithm to find the interrelated components necessary to build the actual physical system.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ajay Kumar Yadav ◽  
Pritam Keshari Sahoo ◽  
Yogendra Kumar Prajapati

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.


2021 ◽  
Vol 19 (2) ◽  
pp. 41-48
Author(s):  
Yu. V. Nemtsov ◽  
I. V. Seryogin ◽  
P. I. Volnov

Base station (BS) is a terminal device of a radio communication network, while railway radio communications play an important role in ensuring safety of passenger and cargo transportation.A proposed method for calculating the performance of base stations in railway digital radio communication networks is intended to calculate for the BS the probabilities of being in certain state.BS was decomposed and such functional elements as circuit groups and a radio frequency path were identified, as well as the central module ensuring the exchange of information with elements of this BS and with other BSs. A detailed study of each element has increased accuracy of the proposed method. Following the Markov model, BS is presented as a system in which all possible states are considered. Models for BS with two and three circuit groups have been constructed. The parameters of each functional element of the model can be obtained through observation over a certain period. The solution of the system of equations for each of the models presented in the article will allow obtaining the values of the system being in a certain state. The obtained characteristics can be used to calculate the reliability of the entire radio communication network, and then to assess quality of service provided to the users of this network.Conclusions are made about the possibilities of using the obtained models when designing new railway communication networks and when calculating quality indices of existing ones. The proposed models can be applied not only to railway radio communication networks but also to mobile communication networks of commercial operators. 


2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Byung-Jin Lee ◽  
Sang-Lim Ju ◽  
Nam-il Kim ◽  
Kyung-Seok Kim

Massive multiple-input multiple-output (MIMO) systems are a core technology designed to achieve the performance objectives defined for 5G wireless communications. They achieve high spectral efficiency, reliability, and diversity gain. However, the many radio frequency chains required in base stations equipped with a high number of transmit antennas imply high hardware costs and computational complexity. Therefore, in this paper, we investigate the use of a transmit-antenna selection scheme, with which the number of required radio frequency chains in the base station can be reduced. This paper proposes two efficient transmit-antenna selection (TAS) schemes designed to consider a trade-off between performance and computational complexity in massive MIMO systems. The spectral efficiency and computational complexity of the proposed schemes are analyzed and compared with existing TAS schemes, showing that the proposed algorithms increase the TAS performance and can be used in practical systems. Additionally, the obtained results enable a better understanding of how TAS affects massive MIMO systems.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Taj Rahman ◽  
Feroz Khan ◽  
Inayat Khan ◽  
Niamat Ullah ◽  
Maha M. Althobaiti ◽  
...  

The Internet of Things (IoT) has brought about various global changes, as all devices will be connected. This article examines the latest 5G solutions for enabling a massive cellular network. It further explored the gaps in previously published articles, demonstrating that to deal with the new challenges. The mobile network must use massive multiple input and output (MIMO), nonorthogonal multiple access (NOMA), orthogonal multiple access (OMA), signal interference cancellation (SIC), channel state information (CSI), and clustering. Furthermore, this article has two objectives such as (1) to introduce the cluster base NOMA to reduce the computational complexity by applying SIC on a cluster, which ultimately results in faster communication and (2) to achieve massive connectivity by proposing massive MIMO with NOMA and OMA. The proposed NOMA clustering technique working principle pairs the close user with the far user; thus, it will reduce computational complexity, which was one such big dilemma in the existing articles. This will specifically help those users that are far away from the base station by maintaining the connectivity. Despite NOMA’s extraordinary benefits, one cannot deny the significance of the OMA; hence, the other objective of the proposed work is to introduce OMA with MIMO in small areas where the user is low in number, it is already in use, and quite cheap. The next important aspect of the proposed work is SIC, which helps remove interference and leads to enhancement in network performance. The simulation result has clearly stated that NOMA has gained a higher rate than OMA: current NOMA users’ power requirement (weak signal user 0.06, strong signal user 0.07), spectral efficiency ratio for P-NOMA and C-NOMA (21%, 5%), signal-to-noise ratio OMA, P-NOMA, C-NOMA (28, 40, 55%), and user rate pairs NOMA, OMA (7, 3), C-NOMA, and massive MIMO NOMA SINR (4.0, 2.5).


2014 ◽  
Vol 1049-1050 ◽  
pp. 2063-2068
Author(s):  
Xiao Tian Wang ◽  
Long Xiang Yang

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.


2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Mohamed Abdul Haleem

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.


2013 ◽  
Vol 284-287 ◽  
pp. 2699-2703 ◽  
Author(s):  
Hung Jen Liao ◽  
Chun Hung Richard Lin ◽  
Kuang Yuan Tung ◽  
Ying Chih Lin ◽  
Cheng Fa Tsai ◽  
...  

Cell planning problem is one of the most important issues in mobile communication networks. To tackle the problem, one should address the location management issue because it significantly affects the cost of cell planning in mobile networks. The partition of location areas is developed to minimize the total costs of considering user location and search operation simultaneously in cellular networks, which has been shown to be NP-complete and is commonly solved by metaheuristics in previous works. In this paper, we propose novel cell planning methods for base stations using genetic algorithms with initialization, local search, and particular mechanisms of area and cell crossovers. Several simulations are conducted on various cell networks with previous, random and real configurations. The simulation results reveal that our schemes are superior to the considered algorithms.


2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Lingjia Liu ◽  
Jianzhong (Charlie) Zhang ◽  
Jae-Chon Yu ◽  
Juho Lee

We consider the applications of multicell transmission schemes to the downlink of future wireless communication networks. A multicell multiple-input multiple output-(MIMOs) based scheme with limited coordination among neighboring base stations (BSs) is proposed to effectively combat the intercell interference by taking advantage of the degreesoffreedom in the spatial domain. In this scheme, mobile users are required to feedback channel-related information to both serving base station and interfering base station. Furthermore, a chordal distance-based compression scheme is introduced to reduce the feedback overhead. The performance of the proposed scheme is investigated through theoretical analysis as well as system level simulations. Both results suggest that the so-called “intercell interference coordination through limited feedback” scheme is a very good candidate for improving the cell-edge user throughput as well as the average cell throughput of the future wireless communication networks.


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