Simplified log likelihood ratio calculation in soft ordered successive interference cancellation for multiple-input multiple-output digital video broadcasting-second generation terrestrial receivers

2014 ◽  
Vol 8 (18) ◽  
pp. 3280-3289 ◽  
Author(s):  
In-Woong Kang ◽  
Youngmin Kim ◽  
Heung Mook Kim ◽  
Young-Jun Lee ◽  
Jae Hyun Seo ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Interference Cancellation ◽  
Second Generation ◽  
Multiple Input Multiple Output ◽  
Successive Interference Cancellation ◽  
Digital Video Broadcasting ◽  
Video Broadcasting ◽  
Multiple Input ◽  
Log Likelihood ◽  
Input Multiple Output

scholarly journals MIMO Detectors Under Correlated Channels

2016 ◽  
Vol 37 (1) ◽  
pp. 3
Author(s):  
Bruno Felipe Costa ◽  
Alex Miyamoto Mussi ◽  
Taufik Abrão
Keyword(s):  
Maximum Likelihood ◽  
Interference Cancellation ◽  
Mean Squared Error ◽  
Multiple Input Multiple Output ◽  
Successive Interference Cancellation ◽  
Correlated Channels ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Multiple Input ◽  
Input Multiple Output

Este artigo analisa o desempenho de detectores com múltiplas antenas transmissoras e múltiplas antenas receptoras (MIMO – multiple-input multiple-output) em canais com desvanecimento correlacionados. Dois esquemas de detecção MIMO denominados erro quadrático médio mínimo (MMSE – minimum mean squared error) – com ou sem a etapa de cancelamento de interferência sucessiva ordenado (OSIC – ordered successive interference cancellation) – e técnica de redução treliça (LR – lattice reduction) são analisados e comparados com o limite de detecção de máxima verossimilhança (ML – maximum likelihood) em cenários específicos de interesse: (a) com incremento da eficiência espectral através do aumento do número de antenas. (b) quando há aumento nos índices de correlação de desvanecimento do canal. Neste contexto, o desempenho do detector ótimo ML-MIMO é utilizado como referência visando caracterizar o comportamento da taxa de erro de bit (BER) destes detectores MIMO e quão próximo esses estão do desempenho ML-MIMO.

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.

scholarly journals Distributed Link Scheduling Algorithm Based on Successive Interference Cancellation in MIMO Wireless Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Junhua Wu ◽  
Dandan Lin ◽  
Guangshun Li ◽  
Yuncui Liu ◽  
Yanmin Yin
Keyword(s):  
Wireless Networks ◽  
Interference Cancellation ◽  
Scheduling Algorithm ◽  
Multiple Input Multiple Output ◽  
Successive Interference Cancellation ◽  
Sensor Nodes ◽  
Link Scheduling ◽  
Mathematical Framework ◽  
Routing And Scheduling ◽  
Input Multiple Output

The performance of multiple input multiple output (MIMO) wireless networks is limited mainly by concurrent interference among sensor nodes. Effective link scheduling algorithms with the technology of successive interference cancellation (SIC) can maximize throughput in MIMO wireless networks. Most previous works on link scheduling in MIMO wireless networks did not consider SIC. In this paper, we propose a MIMO-SIC (MSIC) algorithm under the SINR model. First, a mathematical framework is established for the cross-layer optimization of routing and scheduling, with constraints of traffic balance and link capacity. Second, the interference regions are divided to characterize the level of interference between links. Finally, we propose a distributed link scheduling algorithm based on MSIC to eliminate the interference between competing links in the MIMO network. Experimental results show that the MSIC algorithm can increase the end-to-end throughput per unit by approximately 73% on average compared with non-SIC algorithms.

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