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

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.

scholarly journals Power Optimization of Tilted Tomlinson-Harashima Precoder in MIMO Channels with Imperfect Channel State Information

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Hossein Khaleghi Bizaki ◽  
Morteza Khaleghi Hojaghan ◽  
Seyyed Mohammad Razavizadeh
Keyword(s):  
Channel State Information ◽  
Communication Systems ◽  
Estimation Error ◽  
Multiple Input Multiple Output ◽  
Channel Estimation Error ◽  
Imperfect Channel State Information ◽  
Mimo Channels ◽  
Channel State ◽  
State Information ◽  
Input Multiple Output

This paper concentrates on the designing of a robust Tomlinson-Harashima Precoder (THP) over multiple-input multiple-output (MIMO) channels in wireless communication systems with assumption of imperfect channel state information (CSI) at the transmitter side. With the assumption that the covariance matrix of channel estimation error is available at the transmitter side, we design a THP that presents robustness against channel uncertainties. In the proposed robust THP, the transmit power is further minimized by using the Tilted constellation concept. This power minimization reduces the interchannel Interference (ICI) between subchannels and, furthermore, recovers some part of the THP's power loss. The bit error rate (BER) of the proposed system is further improved by using a power loading technique. Finally, the simulation results compare the performance of our proposed robust THP with a conventional MIMO-THP.

Improved Port Modulation for Multiuser Massive MIMO Systems

2015 ◽  
Vol 7 (4) ◽  
pp. 15-25
Author(s):  
Yujiao He ◽  
Jianing Zhao ◽  
Lijuan Tao ◽  
Fuyu Hou ◽  
Wei Jia
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Channel State ◽  
State Information ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Simulation Results ◽  
Csi Feedback

This paper proposes an improved port modulation (PM) method which can be applied to the multiuser (MU) massive multiple-input multiple-output (MIMO) system. The precoding process of the improved PM can be divided into two parts: port precoding and MU precoding. The methods of the precoding and detection are provided and the performance of the proposed improved PM is simulated and analyzed. Simulation results show that the proposed improved PM system can achieve a satisfying bit error rate (BER) performance with a cutdown channel state information (CSI) feedback.

scholarly journals Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3540 ◽  
Author(s):  
Yurong Wang ◽  
Aijun Liu ◽  
Kui Xu ◽  
Xiaochen Xia
Keyword(s):  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Hardware Complexity ◽  
Mimo Channels ◽  
Channel State ◽  
Active Antennas ◽  
Large Numbers ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Critical Problems

Energy supply and information backhaul are critical problems for wireless sensor networks deployed in remote places with poor infrastructure. To deal with these problems, this paper proposes an airborne massive multiple-input multiple-output (MIMO) system for wireless energy transfer (WET) and information transmission. An air platform (AP) equipped with a two-dimensional rectangular antenna array is employed to broadcast energy and provide wireless access for ground sensors. By exploiting the statistical property of air-terrestrial MIMO channels, the energy and information beamformers are jointly designed to maximize the average received signal-to-interference-plus-noise ratio (SINR), which gives rise to a statistical max-SINR beamforming scheme. The scheme does not rely on the instantaneous channel state information, but still requires large numbers of RF chains at AP. To deal with this problem, a heuristic strongest-path energy and information beamforming scheme is proposed, which can be implemented in the analog-domain with low computational and hardware complexity. The analysis of the relation between the two schemes reveals that, with proper sensor scheduling, the strongest-path beamforming is equivalent to the statistical max-SINR beamforming when the number of AP antennas tends to infinity. Using the asymptotic approximation of average received SINR at AP, the system parameters, including transmit power, number of active antennas of AP and duration of WET phase, are optimized jointly to maximize the system energy efficiency. The simulation results demonstrate that the proposed schemes achieve a good tradeoff between system performance and complexity.

Investigation of the fifth generation non-orthogonal multiple access technique for defense applications using deep learning

2021 ◽  
pp. 154851292110228
Author(s):  
Ravisankar Malladi ◽  
Manoj Kumar Beuria ◽  
Ravi Shankar ◽  
Sudhansu Sekhar Singh
Keyword(s):  
Deep Learning ◽  
Interference Cancellation ◽  
Multiple Access ◽  
Multiple Input Multiple Output ◽  
Optimal Solution ◽  
Channel State ◽  
Fifth Generation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
And Performance

In modern wireless communication scenarios, non-orthogonal multiple access (NOMA) provides high throughput and spectral efficiency for fifth generation (5G) and beyond 5G systems. Traditional NOMA detectors are based on successive interference cancellation (SIC) techniques at both uplink and downlink NOMA transmissions. However, due to imperfect SIC, these detectors are not suitable for defense applications. In this paper, we investigate the 5G multiple-input multiple-output NOMA deep learning technique for defense applications and proposed a learning approach that investigates the communication system’s channel state information automatically and identifies the initial transmission sequences. With the use of the proposed deep neural network, the optimal solution is provided, and performance is much better than the traditional SIC-based NOMA detectors. Through simulations, the analytical outcomes are verified.

scholarly journals SCMA-MIMO system with adaptation to the channel state

2021 ◽  
Vol 2134 (1) ◽  
pp. 012025
Author(s):  
Dmitriy Pokamestov ◽  
Yakov Kryukov ◽  
Eugeniy Rogozhnikov ◽  
Islam Kanatbekuli ◽  
Edgar Dmitriyev
Keyword(s):  
Communication System ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Access ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Network Resources ◽  
Multiple Input ◽  
The Matrix ◽  
High Spectral Efficiency ◽  
Input Multiple Output

Abstract Sparse code multiple access (SCMA) is one of the promising implementations of non-orthogonal multiple access (NOMA) methods. SCMA provides high spectral efficiency and a large number of network resources. We describe a communication system with SCMA, space-time block coding (STBC), multiple input multiple output (MIMO) technology, and orthogonal frequency division multiplexing (OFDM). The architecture of such systems, including algorithms of formation and processing of signals is considered. A method for adapting signals to the state of the spatial channel transmission based on information about the matrix of channel coefficients is proposed. The application of such adaptation allows to compensate the influence of the channel and to reduce the probability of bit errors. We consider the bit error rate (BER) performance of the communication system in different channel models and show the effectiveness of the proposed methods.

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