Spatial Correlation Models of Large-Scale Antenna Topologies Using Maximum Power of Offset Distribution and its Application

Ampoma, Affum Emmanuel; Huang, Yongjun; Gyasi, Kwame Oteng; Tebe, Parfait I.; Ntiamoah-Sarpong, Kwadwo

doi:10.1109/access.2018.2846260

Cited by 11 publications

(25 citation statements)

References 23 publications

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“…In articles [17,18], the authors proposed a model of the MIMO system. The proposed mathematical model is designed to calculate losses on the propagation path for MIMO systems.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…In this model, there is an assumption that the surrounding objects located between the transmitter and the receiver are placed evenly within the two ellipses. , (18) where τ m is the maximum signal delay time, s t is the signal delay time, τ 0 is the minimum signal delay time (line of sight between the transmitter and the receiver), D is the distance between the transmitter and the receiver, c is the wave propagation time. In this model, the minimum average delay time of signal propagation was adopted at the level of 103 nanoseconds, due to the fact that large signal delay values lead to lower antenna correlation.…”

Section: Rementioning

confidence: 99%

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Development of a complex mathematical model of the state of a channel of multi-antenna radio communication systems

Kalantaievska

Kuvshynov

Shyshatskyi

et al. 2019

EEJET

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“…In articles [17,18], the authors proposed a model of the MIMO system. The proposed mathematical model is designed to calculate losses on the propagation path for MIMO systems.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Section: Rementioning

confidence: 99%

Development of a complex mathematical model of the state of a channel of multi-antenna radio communication systems

Kalantaievska

Kuvshynov

Shyshatskyi

et al. 2019

EEJET

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“…For performance improvements and evaluation, GBSM combines channel features such as angle of arrivals, delay profile, tilt angle, path-loss, and so on into the channel models [12], [14]- [16].…”

Section: Literature Reviewmentioning

confidence: 99%

Decode and Forward Coding Scheme for Cooperative Relay NOMA System with Cylindrical Array Transmitter

Tweneboah-Koduah¹,

Affum²,

Kwakye³

et al. 2022

IJACSA

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The Non-Orthogonal Multiple Access (NOMA) technique has enormous potential for wireless communications in the fifth generation (5G) and beyond. Researchers have recently become interested in the combination of NOMA and cooperative relay. Even though geometric-based stochastic channel models (GBSM) have been found to provide better, practical, and realistic channel properties of massive multiple-input multipleoutput (mMIMO) systems, the assessment of Cooperative Relay NOMA (CR-NOMA) with mMIMO system is largely based on correlated-based stochastic channel model (CBSM). We believe that this is a result of computational difficulties. Again, not many discussions have been done in academia about how well CR-NOMA systems perform when large antenna transmitters with the GBSM channel model are used. As a result, it is critical to investigate the mMIMO CR-NOMA system with the GBSM channel model that takes into account channel parameters such as path loss, delay profile, and tilt angle. Moreover, the coexistence of large antenna transmitters and coding methods requires additional research. In this research, we propose a twostage, three-dimension (3D) GBSM mMIMO channel model from the 3GPP, in which the transmitter is modelled as a cylindrical array (CA) to investigate the efficiency of CR-NOMA. By defining antenna elements placement vectors using the actual dimensions of the antenna array and incorporating them into the threedimension (3D) channel model, we were able to increase the analytical tractability of the 3D GBSM. Bit-error rates, achievable rates, and outage probabilities (OP) are investigated utilizing the decode-and-forward (DF) coding method: the results are compared with that of a system using the CBSM channel model. Despite the computational difficulties of the proposed GBSM system, there is no difference in performance between CBSM and GBSM.

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“…Because the wavelength of the terahertz band is very short [20] when the nano-nodes communicate in the terahertz band, a large number of unconnected antennas can be deployed in a limited space to form a large antenna array which provides convenience for the realization of MIMO [21,22]. At present, most researches on terahertz channels are about energy acquisition and information capacity analysis [23][24][25], while there are few studies on multiple inputs and multiple-output (MIMO) in the terahertz band. Because of this, this paper proposes a MIMO model suitable for the terahertz frequency band and analyzes the channel model with traversal capacity as a metric [26,27].…”

Section: Contributionsmentioning

confidence: 99%

MIMO-Terahertz in 6G Nano-Communications: Channel Modeling and Analysis

Bashir¹,

Alsharif²,

Khan³

et al. 2020

Computers, Materials &Amp; Continua

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With the development of wireless mobile communication technology, the demand for wireless communication rate and frequency increases year by year. Existing wireless mobile communication frequency tends to be saturated, which demands for new solutions. Terahertz (THz) communication has great potential for the future mobile communications (Beyond 5G), and is also an important technique for the high data rate transmission in spatial information network. THz communication has great application prospects in military-civilian integration and coordinated development. In China, important breakthroughs have been achieved for the key techniques of THz high data rate communications, which is practically keeping up with the most advanced technological level in the world. Therefore, further intensifying efforts on the development of THz communication have the strategic importance for China in leading the development of future wireless communication techniques and the standardization process of Beyond 5G. This paper analyzes the performance of the MIMO channel in the Terahertz (THz) band and a discrete mathematical method is used to propose a novel channel model. Then, a channel capacity model is proposed by the combination of path loss and molecular absorption in the THz band based on the CSI at the receiver. Simulation results show that the integration of MIMO in the THz band gives better data rate and channel capacity as compared with a single channel.

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Spatial Correlation Models of Large-Scale Antenna Topologies Using Maximum Power of Offset Distribution and its Application

Cited by 11 publications

References 23 publications

Development of a complex mathematical model of the state of a channel of multi-antenna radio communication systems

Development of a complex mathematical model of the state of a channel of multi-antenna radio communication systems

Decode and Forward Coding Scheme for Cooperative Relay NOMA System with Cylindrical Array Transmitter

MIMO-Terahertz in 6G Nano-Communications: Channel Modeling and Analysis

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