Achievable rate and power efficiency in uplink massive MIMO system under antenna correlation

Author(s):  
Varun Kumar ◽  
Sudhansu Arya ◽  
Sarat Kumar Patra
Author(s):  
Weiqiang Tan ◽  
Wei Huang ◽  
Xi Yang ◽  
Zheng Shi ◽  
Wen Liu ◽  
...  

2017 ◽  
Vol 11 (1) ◽  
pp. 20-31 ◽  
Author(s):  
Lifeng Wang ◽  
Hien Quoc Ngo ◽  
Maged Elkashlan ◽  
Trung Q. Duong ◽  
Kai-Kit Wong

2021 ◽  
Author(s):  
Shujuan Yu ◽  
Xinyi Liu ◽  
Jian Cao ◽  
Yun Zhang

Abstract Advantages of the system in this PaperThis paper investigates the uplink of a two-hop massive Multi-input Multi-output (MIMO) relaying system with low-resolution Analog-to-Digital Converters (ADCs) at both relays. Significantly different from previous work, we design a two-hop MIMO system to shorten the distance between each hop, so that there will be Line-of-Sight (LOS) path between relays. This allows signals to be transmitted under Rician channels instead of Rayleigh channels and thus increases the sum achievable rate. Second, we apply low-resolution ADCs at both relays of the system to reduce the energy burden. The main work of this paperThe main work of this paper is as follows. First, assuming the Channel State Information (CSI) is perfect, we use the higher-order statistics to derive the closed-form expression of the uplink sum achievable rate of the two-hop low-resolution ADCs massive MIMO relay system under one-hop Rayleigh channels and two-hop Rician channels. Next, supposing that the number of antennas tends to infinity, we derive the law of power scaling and further achieve the asymptotic closed-form expressions and the asymptotic values under different power scales. Next, we verify the correctness of theoretical analysis with numerical simulation results, and compare the results under one-hop Rayleigh channels and two-hop Rician channels. Finally, we conclude that transmitting signal under two-hop Rician channels can achieve a lower sum achievable rate compared with transmitting under one-hop Rayleigh channels, which means it's more effective to apply two-hop Rician MIMO system. Besides, we conclude that deploying low-cost and energy-efficient low-resolution ADCs at a large-scale relay system can improve the energy efficiency and achieve a fairly considerable sum achievable rate at the same time.


2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Liangliang Wang ◽  
Xiang Chen ◽  
Hongzhou Tan

The potential performance gains promised by massive multi-input and multioutput (MIMO) rely heavily on the access to accurate channel state information (CSI), which is difficult to obtain in practice when channel coherence time is short and the number of mobile users is huge. To make the system with imperfect CSI perform well, we propose a rateless codes-aided massive MIMO scheme, with the aim of approaching the maximum achievable rate (MAR) as well as improving the achieved rate over that based on the fixed-rate codes. More explicitly, a recently proposed family of rateless codes, called spinal codes, are applied to massive MIMO systems, where the spinal codes bring the benefit of approximately achieving the MAR with sufficiently large encoding block size. In addition, the multilevel puncturing and dynamic block-size allocation (MPDBA) scheme is proposed, where the block sizes are determined by user MAR to curb the average retransmission delay for successfully decoding the messages, which further enhances the system retransmission efficiency. Multilevel puncturing, which is MAR dependent, narrows the gap between the system MAR and the related achieved rate. Theoretical analysis is provided to demonstrate that spinal codes with the MPDBA can guarantee the system retransmission efficiency as well as achieved rate, which are also verified by numerical simulations. Finally, a simplified but comparable MIMO testbed with 2 transmit antennas and 2 single-antenna users, based on NI Universal Software Radio Peripheral (USRP) and LabVIEW communication toolkits, is built up to demonstrate the effectiveness of our proposal in realistic wireless channels, which is easy to be extended to massive MIMO scenarios in future.


Author(s):  
Ambala Pradeep Kumar ◽  
Tadisetty Srinivasulu

Massive multiple-input multiple-output (MIMO) is an emerging technology used in next-generation cellular networks. The major challenge in the massive MIMO system is the pilot contamination. The contamination of the pilot sequences causes inaccurate channel estimation leading to huge errors in the transmissions. This paper proposes an approach for pilot contamination reduction in massive MIMO systems. In order to reduce the pilot contamination, a pilot scheduling algorithm is devised by proposing an optimization algorithm named Elephant-based Spider Monkey Optimization (ESMO) for scheduling the pilots. The proposed ESMO is designed by combining Elephant Herding Optimization (EHO) into Spider Monkey Optimization (SMO). The pilot scheduling approach employs proposed ESMO and user degradation for scheduling the pilots. Moreover, the optimal pilot scheduling is carried out using the newly devised fitness function that considers achievable rate using various user grouping parameters, such as utility function, and grouping parameter. Thus, the proposed ESMO-based pilot scheduling and fitness function are responsible for initiating optimal pilot scheduling. The performance of the proposed method is compared with the existing methods, and the proposed ESMO outperformed the existing methods with maximal achievable rate value of 39.257[Formula: see text]bps/Hz, and maximal SINR with value 118.75[Formula: see text]dB, respectively.


2019 ◽  
Vol 23 (3) ◽  
pp. 502-505 ◽  
Author(s):  
Liangyuan Xu ◽  
Xintong Lu ◽  
Shi Jin ◽  
Feifei Gao ◽  
Yongxu Zhu

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 3828-3837
Author(s):  
Tao Zhou ◽  
Kui Xu ◽  
Xiaochen Xia ◽  
Wei Xie ◽  
Jianhui Xu

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