On the performance of the zero-forcing-space-time block coding multiple-input–multiple-output receiver with channel estimation error and error propagation

In this article, three novel systems for wireless sensor networks based on Alamouti decoding were investigated and then compared, which are Alamouti space–time block coding multiple-input single-output/multiple-input multiple-output multicarrier modulation (MCM) system, extended orthogonal space–time block coding multiple-input single-output MCM system, and multiple-input multiple-output system. Moreover, the proposed work is applied over multiple-input multiple-output systems rather than the conventional single-antenna orthogonal chirp division multiplexing systems, based on the discrete fractional cosine transform orthogonal chirp division multiplexing system to mitigate the effect of frequency-selective and time-varying channels, using low-complexity equalizers, specifically by ignoring the intercarrier interference coming from faraway subcarriers and using the LSMR iteration algorithm to decrease the equalization complexity, mainly with long orthogonal chirp division multiplexing symbols, such as the TV symbols. The block diagrams for the proposed systems are provided to simplify the theoretical analysis by making it easier to follow. Simulation results confirm that the proposed multiple-input multiple-output and multiple-input single-output orthogonal chirp division multiplexing systems outperform the conventional multiple-input multiple-output and multiple-input single-output orthogonal frequency division multiplexing systems. Finally, the results show that orthogonal chirp division multiplexing exhibited a better channel energy behavior than classical orthogonal frequency division multiplexing, thus improving the system performance and allowing the system to decrease the equalization complexity.

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Channel capacity analysis of non-orthogonal multiple access and massive multiple-input multiple-output wireless communication networks considering perfect and imperfect channel state information

The Journal of Defense Modeling and Simulation Applications Methodology Technology ◽

10.1177/15485129211000139 ◽

2021 ◽

pp. 154851292110001

Author(s):

Ravi Shankar ◽

Shovon Nandi ◽

Ajay Rupani

Keyword(s):

Multiple Access ◽

Mimo System ◽

Estimation Error ◽

Multiple Input Multiple Output ◽

Channel Estimation Error ◽

Channel State ◽

State Information ◽

Multiple User ◽

Multiple Input ◽

Input Multiple Output

In this paper, we investigate the non-orthogonal multiple access (NOMA) and massive multiple-input multiple-output (M-MIMO) techniques and through simulation, and a comparison is given between the NOMA and orthogonal multiple access techniques. Integrating NOMA with M-MIMO is a very challenging task. In this paper, for a single-cell system, NOMA is integrated with a M-MIMO system for better spectral and energy efficiency. Investigation of the multiple user gain is the focus of this work because the multiple user gain supports simultaneous transmission of multiple users in the case of the M-MIMO system. In this way, the M-MIMO will provide a 100 times channel capacity increase, which results in very high data transmission rate. In the modern communication system, achieving multiple user gain is a very difficult task when channel estimation error is present. The performance of the orthogonal multiple access as well as NOMA system significantly reduced in the presence of channel estimation error. However, most of the current schemes do not work well with imperfect perfect channel state information conditions. Simulation results closely agree with the theoretical outcomes.

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