scholarly journals An Improved End-to-End Autoencoder Based on Reinforcement Learning by Using Decision Tree for Optical Transceivers

Micromachines ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 31
Author(s):  
Qianwu Zhang ◽  
Zicong Wang ◽  
Shuaihang Duan ◽  
Bingyao Cao ◽  
Yating Wu ◽  
...  
Keyword(s):  
Neural Network ◽  
Reinforcement Learning ◽  
Decision Tree ◽  
Bit Error Rate ◽  
Error Rate ◽  
Forward Error Correction ◽  
Adaboost Algorithm ◽  
End To End ◽  
Learning By Using ◽  
Optical Transceivers

In this paper, an improved end-to-end autoencoder based on reinforcement learning by using Decision Tree for optical transceivers is proposed and experimentally demonstrated. Transmitters and receivers are considered as an asymmetrical autoencoder combining a deep neural network and the Adaboost algorithm. Experimental results show that 48 Gb/s with 7% hard-decision forward error correction (HD-FEC) threshold under 65 km standard single mode fiber (SSMF) is achieved with proposed scheme. Moreover, we further experimentally study the Tree depth and the number of Decision Tree, which are the two main factors affecting the bit error rate performance. Experimental research afterwards showed that the effect from the number of Decision Tree as 30 on bit error rate (BER) flattens out under 48 Gb/s for the fiber range from 25 km and 75 km SSMF, and the influence of Tree depth on BER appears to be a gentle point when Tree Depth is 5, which is defined as the optimal depth point for aforementioned fiber range. Compared to the autoencoder based on a Fully-Connected Neural Network, our algorithm uses addition operations instead of multiplication operations, which can reduce computational complexity from 108 to 107 in multiplication and 106 to 108 in addition on the training phase.

scholarly journals The Utilization of Artificial Neural Network Equalizer in Optical Camera Communications

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2826
Author(s):  
Othman Isam Younus ◽  
Navid Bani Hassan ◽  
Zabih Ghassemlooy ◽  
Stanislav Zvanovec ◽  
Luis Nero Alves ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Bit Error Rate ◽  
Error Rate ◽  
Forward Error Correction ◽  
Light Emitting Diode ◽  
Pulse Amplitude ◽  
Eye Diagram ◽  
Artificial Neural

In this paper, we propose and validate an artificial neural network-based equalizer for the constant power 4-level pulse amplitude modulation in an optical camera communications system. We introduce new terminology to measure the quality of the communications link in terms of the number of row pixels per symbol Npps, which allows a fair comparison considering the progress made in the development of the current image sensors in terms of the frame rates and the resolutions of each frame. Using the proposed equalizer, we experimentally demonstrate a non-flickering system using a single light-emitting diode (LED) with Npps of 20 and 30 pixels/symbol for the unequalized and equalized systems, respectively. Potential transmission rates of up to 18.6 and 24.4 kbps are achieved with and without the equalization, respectively. The quality of the received signal is assessed using the eye-diagram opening and its linearity and the bit error rate performance. An acceptable bit error rate (below the forward error correction limit) and an improvement of ~66% in the eye linearity are achieved using a single LED and a typical commercial camera with equalization.

scholarly journals Performance Improvement of Ber Based on Multipath Forward Error Correction Diversity in Wireless Communication Channels

2020 ◽  
Vol 23 (1) ◽  
pp. 159-171
Author(s):  
Ahmad Baheej
Keyword(s):  
Wireless Communication ◽  
Error Correction ◽  
Bit Error Rate ◽  
Error Rate ◽  
Communication Systems ◽  
Forward Error Correction ◽  
Multiple Input Multiple Output ◽  
Wireless Communication Systems ◽  
Forward Error ◽  
Diversity Technique

The multipath phenomenon is a major factor that is continually affected negatively the performance of wireless communication systems. Since the receiver gets different copies of the transmitted signal from various paths at different times. Consequently, destructive or constructive interference can occur. Therefore, the performance of wireless communication systems is poor in term of bit error rate. This phenomenon can be taken as an advantage if the multiple – input – multiple – output antenna systems are employed at both transmitter and receiver sides (antenna diversity) to improve the bit error rate performance. This paper focuses on the combination of multipath forward error correction diversity technique with vertical-Bell laboratories layered space-time coding. This will lead to enhance the bit error rate in wireless communication systems. The proposed system used Rayleigh and additive white Gaussian noise as two different channel models. The multipath forward error correction diversity technique treats the multipath propagated signals as unessential copies, to utilise them to enhance the bit error rate limitation in the multiple – input – multiple – output systems. The simulation results showed that the performance of the proposed system can be gradually improved by increasing the number of utilised multipath signals in the multipath forward error correction diversity technique

scholarly journals Error Detection in Turbo Decoding using Neural Network

2019 ◽  
Vol 9 (1S) ◽  
pp. 218-221
Keyword(s):  
Neural Network ◽  
Bit Error Rate ◽  
Error Rate ◽  
Error Detection ◽  
Turbo Codes ◽  
Iterative Decoding ◽  
Turbo Decoding ◽  
Turbo Decoder ◽  
The Neural Network ◽  
Turbo Encoder

In this paper reduction of errors in turbo decoding is done using neural network. Turbo codes was one of the first thriving attempt for obtaining error correcting performance in the vicinity of the theoretical Shannon bound of –1.6 db. Parallel concatenated encoding and iterative decoding are the two techniques available for constructing turbo codes. Decrease in Eb/No necessary to get a desired bit-error rate (BER) is achieved for every iteration in turbo decoding. But the improvement in Eb/No decreases for each iteration. From the turbo encoder, the output is taken and this is added with noise, when transmitting through the channel. The noisy data is fed as an input to the neural network. The neural network is trained for getting the desired target. The desired target is the encoded data. The turbo decoder decodes the output of neural network. The neural network help to reduce the number of errors. Bit error rate of turbo decoder trained using neural network is less than the bit error rate of turbo decoder without training.

scholarly journals A General Rate K/N Convolutional Decoder Based on Neural Networks with Stopping Criterion

2009 ◽  
Vol 2009 ◽  
pp. 1-11 ◽  
Author(s):  
Johnny W. H. Kao ◽  
Stevan M. Berber ◽  
Abbas Bigdeli
Keyword(s):  
Neural Network ◽  
Bit Error Rate ◽  
Error Rate ◽  
Iterative Decoding ◽  
Viterbi Algorithm ◽  
Convolutional Code ◽  
Rate Transmission ◽  
Neural Network Structure ◽  
Data Rate Transmission ◽  
Novel Algorithm

A novel algorithm for decoding a general rate K/N convolutional code based on recurrent neural network (RNN) is described and analysed. The algorithm is introduced by outlining the mathematical models of the encoder and decoder. A number of strategies for optimising the iterative decoding process are proposed, and a simulator was also designed in order to compare the Bit Error Rate (BER) performance of the RNN decoder with the conventional decoder that is based on Viterbi Algorithm (VA). The simulation results show that this novel algorithm can achieve the same bit error rate and has a lower decoding complexity. Most importantly this algorithm allows parallel signal processing, which increases the decoding speed and accommodates higher data rate transmission. These characteristics are inherited from a neural network structure of the decoder and the iterative nature of the algorithm, that outperform the conventional VA algorithm.

scholarly journals Performance analysis of an orbital angular momentum multiplexed amplify-and-forward radio relay chain with inter-modal crosstalk

2019 ◽  
Vol 6 (1) ◽  
pp. 181063 ◽  
Author(s):  
B. Allen ◽  
D. Simmons ◽  
T. D. Drysdale ◽  
J. Coon
Keyword(s):  
Angular Momentum ◽  
Performance Analysis ◽  
Orbital Angular Momentum ◽  
Bit Error Rate ◽  
Error Rate ◽  
Data Streams ◽  
Spectral Efficiency ◽  
Amplify And Forward ◽  
Parallel Data ◽  
End To End

The end-to-end spectral efficiency and bit error rate (BER) of an amplify-and-forward (AF) radio relay chain employing orbital angular momentum (OAM) multiplexing is presented. The inherent divergence of a beam carrying OAM is overcome by means of a lens. Modelled and measured inter-modal crosstalk levels are incorporated into the analysis. The results show that an end-to-end spectral efficiency of up to 8 bits s −1 Hz −1 is achievable using four OAM modes to multiplex four parallel data streams over 20 hops, provided that the detrimental effects of inter-modal crosstalk are mitigated. The spectral efficiency is expected to scale further by using more OAM modes. The BER profile along the relay chain is analysed for each of the four OAM modes.

scholarly journals Performance Enhancement of Bit Error Rate with Increased Capacity using Modified SIC-MUD for Polar Code based OFDM-IDMA System for 5G

2019 ◽  
Vol 8 (9S3) ◽  
pp. 192-200
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Interference Cancellation ◽  
Forward Error Correction ◽  
Performance Enhancement ◽  
Detection Algorithm ◽  
Available Bandwidth ◽  
Polar Code ◽  
Extensive Growth ◽  
Forward Error

In the era of mobile data revolution there is a mass-market of smart phones culminating into an extensive growth in mobile services and applications. However, bandwidth is limited and valuable resource available. In this paper hybrid combination of OFDM-IDMA system is proposed using polar code as forward error correction code and Gold code based interleaver. It presents a method to improvebit error rate with 10 users and normalizedcarrier frequency offsets of 0.1 to 0.5.The simulation is done in the presence of Rayleigh and AWGN channel with 64 QAM modulation technique. A modified successive interference cancellation multi-user detection algorithm is proposed to cater multiple access interference.It is observed that proposed system withnormalized CFO of 0.1 for10 users at required SNR of 15 dB enhances the bit error rate to 1.021*10-4over available existing systems. Hence the capacity of the system and data rate increases by three times to support multimedia application within available bandwidth.

Research on Modulations of Wireless Optical Communication System Based on RS Code under Weak Turbulence Atmosphere Channel

2014 ◽  
Vol 556-562 ◽  
pp. 4945-4949
Author(s):  
Yang Liu ◽  
Guoan Zhang
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Forward Error Correction ◽  
Error Rates ◽  
Pulse Interval ◽  
Pulse Position Modulation ◽  
Weak Turbulence ◽  
Rate Performance ◽  
Free Space Optical ◽  
Digital Pulse

The free space optical (FSO) system model is analyzed based on on-off keying (OOK), pulse position modulation (PPM), differential pulse position modulation (DPPM) and digital pulse interval modulation (DPIM) under the weak turbulence atmosphere. To improve the system performance, one effective way is to use forward error correction (FEC).The bit error rate (BER) calculating formula of uncoded system is derived under all above the modulations firstly, then as a benchmark, under the case of independent with identical distribution, the average bit error rates of RS coded system are derived, respectively. Simulations of the average bit error rate performance of these systems are done. Simulation results show that, PPM has the best bit error rate performance, RS coded is efficient to get the code gain and to improve jamming-rejection capability of system.

scholarly journals Bit error rate performance analysis of AC-MAP in multiple input single output wireless relay network

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Taha A. Khalaf ◽  
Hazem Mohammed
Keyword(s):  
Closed Form ◽  
Bit Error Rate ◽  
Error Rate ◽  
Relay Network ◽  
Closed Form Expression ◽  
Channel Noise ◽  
Single Output ◽  
Multiple Input ◽  
End To End ◽  
Map Decoder

AbstractIn this paper, we propose a joint decoding scheme called AC-MAP decoder for multiple input single output (MISO) wireless cooperative communication network that consists of single source, single relay, and single destination. The proposed scheme is based on both Alamouti combining (AC) scheme and maximum a posteriori (MAP) decoder and is used to estimate the data at the destination. The AC-MAP decoder is optimal in the sense that it minimizes the end-to-end bit error rate (BER). In order to analyze performance of the proposed decoder, we derive a closed form expression for the upper bound (UB) on the end-to-end error probability. Distances between system nodes, transmit energy, and channel noise and fading effects are considered in the derivation of the UB. Numerical results show that the closed form UB is very tight and it almost coincides with the exact BER results obtained from simulations. Therefore, we use the derived UB expression to study the effects of the relay position on the BER performance and to find the optimal location of the relay node.

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