Time reversal multiple-input/multiple-output acoustic communication enhanced by parallel interference cancellation

2012 ◽  
Vol 131 (1) ◽  
pp. 281-291 ◽  
Author(s):  
Aijun Song ◽  
Mohsen Badiey
Keyword(s):  
Acoustic Communication ◽  
Time Reversal ◽  
Interference Cancellation ◽  
Multiple Input Multiple Output ◽  
Parallel Interference Cancellation ◽  
Multiple Input ◽  
Input Multiple Output

Multiuser and multiple-input-multiple-output underwater acoustic communication using time reversal

2016 ◽  
Vol 140 (4) ◽  
pp. 3230-3230
Author(s):  
Takuya Shimura ◽  
Yukihiro Kida ◽  
Mitsuyasu Deguchi ◽  
Kohji Meguro ◽  
Yoshitaka Watanabe ◽  
...  
Keyword(s):  
Acoustic Communication ◽  
Time Reversal ◽  
Multiple Input Multiple Output ◽  
Underwater Acoustic Communication ◽  
Underwater Acoustic ◽  
Multiple Input ◽  
Input Multiple Output

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 Efficient Power Allocation for LDPC-Coded MIMO Systems

2011 ◽  
pp. 127-133
Author(s):  
Layak Ali Sd ◽  
K. Kishan Rao ◽  
M. Sushanth Bab
Keyword(s):  
Interference Cancellation ◽  
Communication Systems ◽  
Mimo Systems ◽  
Geometric Mean ◽  
Multiple Input Multiple Output ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Coded Systems ◽  
Efficient Power ◽  
Q Function

In this papers an efficient ordering scheme for an ordered successive interference cancellation detector is determined under the bit error rate minimization criterion for multiple-input multiple-output(MIMO) communication systems using transmission power control. From the convexity of the Q-function, we evaluate the choice of suitable quantization characteristics for both the decoder messages and the received samples in Low Density Parity Check (LDPC)-coded systems using M-QAM schemes. We derive the ordering strategy that makes the channel gains converge to their geometric mean. Based on this approach, the fixed ordering algorithm is first designed, for which the geometric mean is used for a constant threshold using correlation among ordering results.

scholarly journals A MMSE-based Beamforming Algorithm for MIMO Point-to-Point Full-Duplex Communication Systems

2017 ◽  
Vol 1 (3) ◽  
pp. 72
Author(s):  
Tu Bui-Thi-Minh ◽  
Xung Le ◽  
Vien Nguyen-Duy-Nhat
Keyword(s):  
Interference Cancellation ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Full Duplex ◽  
Rate Maximization ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Point To Point ◽  
Transmitting Antenna ◽  
Beamforming Algorithm

In this paper, we focus on the precoding design for sum rate maximization while considering the effects of residual SI for point – to-point multiple input/multiple output (MIMO) Full-Duplex systems. The MMSE-based beamforming algorithm was proposed to cancel the SI. The results shown that, the self-interference cancellation is done by matrix precoding at the transmitter if the total number of transmitting antenna of two nodes is greater than the number of receiving antenna of one node. The Bit Error Rate (BER) was also evaluated in the simulation.

Multiple-Input–Multiple-Output Coherent Time Reversal Communications in a Shallow-Water Acoustic Channel

2006 ◽  
Vol 31 (1) ◽  
pp. 170-178 ◽  
Author(s):  
H.C. Song ◽  
P. Roux ◽  
W.S. Hodgkiss ◽  
W.A. Kuperman ◽  
T. Akal ◽  
...  
Keyword(s):  
Shallow Water ◽  
Time Reversal ◽  
Multiple Input Multiple Output ◽  
Acoustic Channel ◽  
Multiple Input ◽  
Input Multiple Output
Sign in / Sign up

Export Citation Format

Share Document