scholarly journals Complex-Valued Phase Transmittance RBF Neural Networks for Massive MIMO-OFDM Receivers

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8200
Author(s):  
Jonathan Aguiar Soares ◽  
Kayol Soares Mayer ◽  
Fernando César Comparsi de Castro ◽  
Dalton Soares Arantes
Keyword(s):  
Computational Complexity ◽  
Maximum Likelihood ◽  
Cost Effective ◽  
Performance Comparison ◽  
Practical Implementation ◽  
Limiting Factor ◽  
Rbf Neural Networks ◽  
Maximum Likelihood Decoding ◽  
Mimo Channels ◽  
Mimo Ofdm

Multi-input multi-output (MIMO) transmission schemes have become the techniques of choice for increasing spectral efficiency in bandwidth-congested areas. However, the design of cost-effective receivers for MIMO channels remains a challenging task. The maximum likelihood detector can achieve excellent performance—usually, the best performance—but its computational complexity is a limiting factor in practical implementation. In the present work, a novel MIMO scheme using a practically feasible decoding algorithm based on the phase transmittance radial basis function (PTRBF) neural network is proposed. For some practical scenarios, the proposed scheme achieves improved receiver performance with lower computational complexity relative to the maximum likelihood decoding, thus substantially increasing the applicability of the algorithm. Simulation results are presented for MIMO-OFDM under 5G wireless Rayleigh channels so that a fair performance comparison with other reference techniques can be established.

Reducing Computational Complexity and Enhancing Performance of IKSD Algorithm for Encoded MIMO Systems

2016 ◽  
Vol 2 (3) ◽  
pp. 636 ◽  
Author(s):  
Mohammed Qasim Sulttan
Keyword(s):  
Computational Complexity ◽  
Maximum Likelihood ◽  
High Performance ◽  
Mimo Systems ◽  
Practical Implementation ◽  
Mimo Detection ◽  
Detection Algorithms ◽  
Sphere Detection ◽  
Manhattan Metric ◽  
Main Challenge

<p>The main challenge in MIMO systems is how to design the MIMO detection algorithms with lowest computational complexity and high performance that capable of accurately detecting the transmitted signals. In last valuable research results, it had been proved the Maximum Likelihood Detection (MLD) as the optimum one, but this algorithm has an exponential complexity especially with increasing of a number of transmit antennas and constellation size making it an impractical for implementation. However, there are alternative algorithms such as the K-best sphere detection (KSD) and Improved K-best sphere detection (IKSD) which can achieve a close to Maximum Likelihood (ML) performance and less computational complexity. In this paper, we have proposed an enhancing IKSD algorithm by adding the combining of column norm ordering (channel ordering) with Manhattan metric to enhance the performance and reduce the computational complexity. The simulation results show us that the channel ordering approach enhances the performance and reduces the complexity, and Manhattan metric alone can reduce the complexity. Therefore, the combined channel ordering approach with Manhattan metric enhances the performance and much reduces the complexity more than if we used the channel ordering approach alone. So our proposed algorithm can be considered a feasible complexity reduction scheme and suitable for practical implementation.</p>

Direct ammonia fueled solid oxide fuel cells: A comprehensive review on challenges, opportunities and future outlooks

2020 ◽  
pp. 70-91 ◽  
Author(s):  
Molla Asmare ◽  
Mustafa Ilbas
Keyword(s):  
Electric Power ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Clean Energy ◽  
Performance Comparison ◽  
Optimum Operating ◽  
Practical Implementation ◽  
Human Society ◽  
Energy Access ◽  
Green Fuel

Nowadays, the most decisive challenges we are fronting are perfectly clean energy making for equitable and sustainable modern energy access, and battling the emerging alteration of the climate. This is because, carbon-rich fuels are the fundamental supply of utilized energy for strengthening human society, and it will be sustained in the near future. In connection with this, electrochemical technologies are an emerging and domineering tool for efficiently transforming the existing scarce fossil fuels and renewable energy sources into electric power with a trivial environmental impact. Compared with conventional power generation technologies, SOFC that operate at high temperature is emerging as a frontrunner to convert the fuels chemical energy into electric power and permits the deployment of varieties of fuels with negligible ecological destructions. According to this critical review, direct ammonia is obtained as a primary possible choice and price-effective green fuel for T-SOFCs. This is because T-SOFCs have higher volumetric power density, mechanically stable, and high thermal shocking resistance. Also, there is no sealing issue problem which is the chronic issues of the planar one. As a result, the toxicity of ammonia to use as a fuel is minimized if there may be a leakage during operation. It is portable and manageable that can be work everywhere when there is energy demand. Besides, manufacturing, onboard hydrogen deposition, and transportation infrastructure connected snags of hydrogen will be solved using ammonia. Ammonia is a low-priced carbon-neutral source of energy and has more stored volumetric energy compared with hydrogen. Yet, to utilize direct NH3 as a means of hydrogen carrier and an alternative green fuel in T-SOFCs practically determining the optimum operating temperatures, reactant flow rates, electrode porosities, pressure, the position of the anode, thickness and diameters of the tube are still requiring further improvement. Therefore, mathematical modeling ought to be developed to determine these parameters before planning for experimental work. Also, a performance comparison of AS, ES, and CS- T-SOFC powered with direct NH3 will be investigated and best-performed support will be carefully chosen for practical implementation and an experimental study will be conducted for verification based on optimum parameter values obtained from numerical modeling.

Capacity Analysis for Correlated Multi-Hop MIMO Channels under Colored Noise

2015 ◽  
Vol 1 ◽  
pp. 41
Author(s):  
Nguyen N. Tran ◽  
Ha X. Nguyen
Keyword(s):  
Computational Complexity ◽  
Mutual Information ◽  
Closed Form Solution ◽  
Optimal Solution ◽  
Form Solution ◽  
Maximization Problem ◽  
Capacity Analysis ◽  
Mimo Channels ◽  
Average Mutual Information ◽  
Channel Output

A capacity analysis for generally correlated wireless multi-hop multi-input multi-output (MIMO) channels is presented in this paper. The channel at each hop is spatially correlated, the source symbols are mutually correlated, and the additive Gaussian noises are colored. First, by invoking Karush-Kuhn-Tucker condition for the optimality of convex programming, we derive the optimal source symbol covariance for the maximum mutual information between the channel input and the channel output when having the full knowledge of channel at the transmitter. Secondly, we formulate the average mutual information maximization problem when having only the channel statistics at the transmitter. Since this problem is almost impossible to be solved analytically, the numerical interior-point-method is employed to obtain the optimal solution. Furthermore, to reduce the computational complexity, an asymptotic closed-form solution is derived by maximizing an upper bound of the objective function. Simulation results show that the average mutual information obtained by the asymptotic design is very closed to that obtained by the optimal design, while saving a huge computational complexity.

Maximum likelihood decoding of RLL-FEC array codes on partial response channels

1993 ◽  
Vol 29 (16) ◽  
pp. 1406 ◽  
Author(s):  
G.S. Markarian ◽  
M. Naderi ◽  
B. Honary ◽  
A. Popplewell ◽  
J.J. O'Reilly
Keyword(s):  
Maximum Likelihood ◽  
Partial Response ◽  
Maximum Likelihood Decoding ◽  
Partial Response Channels ◽  
Array Codes
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