On potential channel capacity of massive MIMO array within small finite space

2013 ◽  
Author(s):  
Kentaro Murata ◽  
Naoki Honma
Keyword(s):  
Channel Capacity ◽  
Massive Mimo ◽  
Finite Space

scholarly journals Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 301
Author(s):  
Samarendra Nath Sur ◽  
Rabindranath Bera ◽  
Akash Kumar Bhoi ◽  
Mahaboob Shaik ◽  
Gonçalo Marques
Keyword(s):  
Channel Capacity ◽  
Massive Mimo ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Mimo System ◽  
Correlation Effect ◽  
Performance Comparison ◽  
Lattice Reduction ◽  
Detection Algorithms ◽  
Minimum Mean Squared Error

Massive multi-input-multi-output (MIMO) systems are the future of the communication system. The proper design of the MIMO system needs an appropriate choice of detection algorithms. At the same time, Lattice reduction (LR)-aided equalizers have been well investigated for MIMO systems. Many studies have been carried out over the Korkine–Zolotareff (KZ) and Lenstra–Lenstra–Lovász (LLL) algorithms. This paper presents an analysis of the channel capacity of the massive MIMO system. The mathematical calculations included in this paper correspond to the channel correlation effect on the channel capacity. Besides, the achievable gain over the linear receiver is also highlighted. In this study, all the calculations were further verified through the simulated results. The simulated results show the performance comparison between zero forcing (ZF), minimum mean squared error (MMSE), integer forcing (IF) receivers with log-likelihood ratio (LLR)-ZF, LLR-MMSE, KZ-ZF, and KZ-MMSE. The main objective of this work is to show that, when a lattice reduction algorithm is combined with the convention linear MIMO receiver, it improves the capacity tremendously. The same is proven here, as the KZ-MMSE receiver outperforms its counterparts in a significant margin.

scholarly journals Joint Design of Massive MIMO Precoder and Security Scheme for Multiuser Scenarios under Reciprocal Channel Conditions

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Gustavo Anjos ◽  
Daniel Castanheira ◽  
Adão Silva ◽  
Atílio Gameiro ◽  
Marco Gomes ◽  
...  
Keyword(s):  
Channel Capacity ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Wireless Channel ◽  
Joint Design ◽  
Security Scheme ◽  
Working Principle ◽  
Transmitted Signal ◽  
Intended Receiver

The exploration of the physical layer characteristics of the wireless channel is currently the object of intensive research in order to develop advanced secrecy schemes that can protect information against eavesdropping attacks. Following this line of work, in this manuscript we consider a massive MIMO system and jointly design the channel precoder and security scheme. By doing that we ensure that the precoding operation does not reduce the degree of secrecy provided by the security scheme. The fundamental working principle of the proposed technique is to apply selective random rotations in the transmitted signal at the antenna level in order to achieve a compromise between legitimate and eavesdropper channel capacities. These rotations use the phase of the reciprocal wireless channel as a common random source between the transmitter and the intended receiver. To assess the security performance, the proposed joint scheme is compared with a recently proposed approach for massive MIMO systems. The results show that, with the proposed joint design, the number of antenna elements does not influence the eavesdropper channel capacity, which is proved to be equal to zero, in contrast to previous approaches.

scholarly journals On the MIMO Capacity for Distributed System under Composite Rayleigh/Rician Fading and Shadowing

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Santiago González-Aurioles ◽  
J. L. Padilla ◽  
P. Padilla ◽  
Juan F. Valenzuela-Valdés ◽  
Juan C. Gonzalez-Macias
Keyword(s):  
Channel Capacity ◽  
Massive Mimo ◽  
Rayleigh Fading ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Rician Fading ◽  
Short Term ◽  
Multiple Input ◽  
Fading And Shadowing ◽  
The One

Wireless channels are commonly affected by short-term fading and long-term fading (shadowing). The shadowing effects must be taken into account also when mobility is present in the wireless scenario. Using a composite fading model, the total channel capacity can be studied for a scenario with short-term Rayleigh fading along with shadowing. This work provides quantitative results for these kinds of scenarios with Rayleigh fading and shadowing, considering also multiple-input and multiple-output systems, which have not been previously reported. In addition, the channel capacity has been studied in depth in its relation with the shadowing level, signal to noise ratio, and the number of elements in the multiple-input and multiple-output system. Moreover, the channel performance with shadowing has been compared to the one without it. Furthermore, Rician model with shadowing is studied and its results are reported. In addition, correlated and experimental results are provided. It is identified that the distributed MIMO systems can benefit from shadowing in Rician channels. This advantage has not been reported previously. This type of fading is proposed for massive MIMO by others and our results open the door to emulate massive MIMO on a reverberation chamber.

A Review of Massive Multiple Input Multiple Output for 5G Communication: Benefits and Challenges

2020 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Shaik Nilofer ◽  
Keyword(s):  
Wireless Communication ◽  
Channel Capacity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Primary Advantage ◽  
Time Division

Massive MIMO (mMIMO) systems become a primary advantage to overcome the problem of bandwidth restrictions. It improves the channel capacity of remote systems.The paper reviews about mMIMO systems. mMIMO consists of several number of antennas at base station (BS) which improves spectrum efficacy. The extra benefit of the mMIMO system is that the components cost is low because of utilization of less power components. The paper also discusses about the channel estimation at the BS and generally time division mode (TDD) is assumed for mMIMO systems. The paper also discusses system model, benefits for 5G wireless communication and its challenges.

Channel capacity investigation of a linear massive MIMO system using spherical wave model in LOS scenarios

2016 ◽  
Vol 59 (2) ◽  
pp. 1-15 ◽  
Author(s):  
Liu Liu ◽  
David W. Matolak ◽  
Cheng Tao ◽  
Yongzhi Li ◽  
Bo Ai ◽  
...  
Keyword(s):  
Channel Capacity ◽  
Massive Mimo ◽  
Mimo System ◽  
Spherical Wave ◽  
Wave Model

A Review of Massive Multiple Input Multiple Output for 5G Communication: Benefits and Challenges

2020 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Shaik Nilofer
Keyword(s):  
Wireless Communication ◽  
Channel Capacity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Primary Advantage ◽  
Time Division

Massive MIMO (mMIMO) systems become a primary advantage to overcome the problem of bandwidth restrictions. It improves the channel capacity of remote systems.The paper reviews about mMIMO systems. mMIMO consists of several number of antennas at base station (BS) which improves spectrum efficacy. The extra benefit of the mMIMO system is that the components cost is low because of utilization of less power components. The paper also discusses about the channel estimation at the BS and generally time division mode (TDD) is assumed for mMIMO systems. The paper also discusses system model, benefits for 5G wireless communication and its challenges.

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