scholarly journals Rate-compatible LDPC convolutional codes over non-gaussian noise channel

2020 ◽  
Vol 309 ◽  
pp. 01010
Author(s):  
Qiang Liu
Keyword(s):  
Gaussian Noise ◽  
Iterative Decoding ◽  
Belief Propagation ◽  
Additive White Gaussian Noise ◽  
Convolutional Codes ◽  
Gaussian Mixture ◽  
Performance Study ◽  
Shift Keying ◽  
Non Gaussian ◽  
The Impact

This paper is aimed to study the characteristics of the underwater acoustic channel with non-Gaussian noise channel. And Gaussian mixture model (GMM) is utilized to fit the background noise over the non-Gaussian noise channel. Furthermore, coding techniques which use a sequence of rate-compatible low-density parity-check (RC-LDPC) convolutional codes with separate rates are constructed based on graph extension method. The performance study of RC-LDPC convolutional codes over non-Gaussian noise channel and the additive white Gaussian noise (AWGN) channel is performed. Study implementation of simulation is that modulation with binary phase shift keying (BPSK), and iterative decoding based on pipeline log-likelihood rate belief propagation (LLRBP) algorithm. Finally, it is shown that RC-LDPC convolutional codes have good bit-rate-error (BER) performance and can effectively reduce the impact of noise.

M-Ary Alpha-Stable Noise Modulation in Spread-Spectrum Communication

2015 ◽  
Vol 14 (03) ◽  
pp. 1550022 ◽  
Author(s):  
Mehmet Emre Cek
Keyword(s):  
Gaussian Noise ◽  
Spread Spectrum ◽  
Additive White Gaussian Noise ◽  
Characteristic Exponent ◽  
Random Signal ◽  
Spread Spectrum Communication ◽  
Order Moment ◽  
Gaussian Density ◽  
Shift Keying ◽  
Non Gaussian

In this paper, a spread-spectrum communication system based on a random carrier is proposed which transmits M-ary information. The random signal is considered as a single realization of a random process taken from prescribed symmetric α-stable (SαS) distribution that carries digital M-ary information to be transmitted. Considering the noise model in the channel as additive white Gaussian noise (AWGN), the transmitter sends the information carrying random signal from non-Gaussian density. Alpha-stable distribution is used to encode the M-ary message. Inspired by the chaos shift keying techniques, the proposed method is called M-ary symmetric alpha-stable differential shift keying (M-ary SαS-DSK). The main purpose of preferring non-Gaussian noise instead of conventional pseudo-noise (PN) sequence is to overcome the drawback of self-repeating noise-like sequences which are detectable due to the periodic behavior of the autocorrelation function of PN sequences. Having infinite second order moment in α-stable random carrier offers secrecy of the information due to the non-constant autocorrelation behavior. The bit error rate (BER) performance of the proposed method is illustrated by Monte Carlo simulations with respect to various characteristic exponent values and different data length.

scholarly journals 3D-MIMO Channel Estimation under Non-Gaussian Noise with Unknown PDF

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 316 ◽  
Author(s):  
Wei Chen ◽  
Feng Li ◽  
Yiting Peng
Keyword(s):  
Channel Estimation ◽  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Gaussian Mixture ◽  
Mimo Channel ◽  
Estimation Model ◽  
Channel Matrix ◽  
Common Support ◽  
3D Mimo ◽  
Non Gaussian

Three-dimensional-multiple-input-multiple-output (3D-MIMO) technology has attracted a lot of attention in the field of wireless communication. Most of the research mainly focuses on channel estimation model which is affected by additive-white-Gaussian-noise (AWGN). However, under the influence of some specified factors, such as electronic interference and man-made noise, the noise of the channel does not follow the Gaussian distribution anymore. Sometimes, the probability density function (PDF) of the noise is unknown at the receiver. Based on this reality, this paper tries to address the problem of channel estimation under non-Gaussian noise with unknown PDF. Firstly, the common support of angle domain channel matrix is estimated by compressed sensing (CS) reconstruction algorithm and a decision rule. Secondly, after modeling the received signal as a Gaussian mixture model (GMM), a data pruning algorithm is exerted to calculate the order of GMM. Lastly, an expectation maximization (EM) algorithm for linear regression is implemented to estimate the the channel matrix iteratively. Furthermore, sparsity, not only in the time domain, but in addition in the angle domain, is utilized to improve the channel estimation performance. The simulation results demonstrate the merits of the proposed algorithm compared with the traditional ones.

scholarly journals Threshold Computation for Spatially Coupled Turbo-Like Codes on the AWGN Channel

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 240
Author(s):  
Muhammad Umar Farooq ◽  
Alexandre Graell i Amat ◽  
Michael Lentmaier
Keyword(s):  
Gaussian Noise ◽  
Belief Propagation ◽  
Additive White Gaussian Noise ◽  
Maximum A Posteriori ◽  
Prediction Methods ◽  
Threshold Analysis ◽  
A Posteriori ◽  
Awgn Channel ◽  
Efficient Prediction ◽  
Binary Erasure Channel

In this paper, we perform a belief propagation (BP) decoding threshold analysis of spatially coupled (SC) turbo-like codes (TCs) (SC-TCs) on the additive white Gaussian noise (AWGN) channel. We review Monte-Carlo density evolution (MC-DE) and efficient prediction methods, which determine the BP thresholds of SC-TCs over the AWGN channel. We demonstrate that instead of performing time-consuming MC-DE computations, the BP threshold of SC-TCs over the AWGN channel can be predicted very efficiently from their binary erasure channel (BEC) thresholds. From threshold results, we conjecture that the similarity of MC-DE and predicted thresholds is related to the threshold saturation capability as well as capacity-approaching maximum a posteriori (MAP) performance of an SC-TC ensemble.

scholarly journals Design and Implementation of a Chaotic Scheme in Additive White Gaussian Noise Channel

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Nizar Al Bassam ◽  
Oday Jerew
Keyword(s):  
Bit Error Rate ◽  
Gaussian Noise ◽  
Chaotic Systems ◽  
Gaussian Approximation ◽  
Additive White Gaussian Noise ◽  
Design And Implementation ◽  
Shift Keying ◽  
Transmitted Signal ◽  
Chaos Shift Keying ◽  
Channel Environment

A new chaotic scheme named Flipped Chaotic On-Off Keying (FCOOK) is proposed for binary transmission. In FCOOK, the low correlation value between the stationary signal and its mirrored version is utilized. Transmitted signal for binary 1 is a chaotic segment added to its time flipped (mirrored) version within one bit duration, while in binary 0, no transmission takes place within the same bit duration. The proposed scheme is compared with the standard chaotic systems: Differential Chaos Shift Keying (DCSK) and Correlation Delay Shift Keying (CDSK). The Bit Error Rate (BER) of FCOOK is studied analytically based on Gaussian approximation method. Results show that the BER performance of FCOOK outperforms DCSK and CDSK in AWGN channel environment and with variousEb/Nolevels. Additionally, FCOOK offers a double bit rate compared with the standard DCSK.

scholarly journals Evaluasi Modulasi MFSK untuk Transmisi Data Melalui Kanal Suara GSM

Jurnal INKOM ◽  
2014 ◽  
Vol 8 (1) ◽  
pp. 37
Author(s):  
Rika Sustika ◽  
Oka Mahendra
Keyword(s):  
Mobile Communication ◽  
Bit Error Rate ◽  
Error Rate ◽  
Gaussian Noise ◽  
Linear Prediction ◽  
Signal To Noise Ratio ◽  
Additive White Gaussian Noise ◽  
Signal To Noise ◽  
Global System ◽  
Shift Keying

Pada tulisan ini, dievaluasi performansi skema modulasi MFSK (M-ary Frequency Shift Keying) untuk aplikasi pengiriman data melalui kanal suara GSM (Global System for Mobile Communication). Parameter yang dievaluasi berupa kesalahan bit trasmisi yang dinyatakan dengan laju kesalahan bit atau bit error rate (BER). Evaluasi ini dilakukan untuk menentukan besarnya orde M yang akan dipilih pada aplikasi pengiriman data digital melalui kanal suara GSM. Pada proses simulasi, data digital dikodekan menjadi simbol-simbol lalu dimodulasi menggunakan modulator MFSK menjadi data menyerupai pembicaraan (suara). Suara yang dihasilkan dikodekan dengan algoritma CELP (Code Excited Linear Prediction), kemudian dikirimkan melalui udara yang dimodelkan sebagai kanal AWGN (Additive White Gaussian Noise). Di sisi penerima, sinyal terima yang menyerupai suara ini didemodulasi dan dikonversi kembali menjadi data digital. Dari simulasi menggunakan Eb/No (signal to noise ratio) sebesar 6 dB, diperoleh laju bit 2,5 kbps dengan BER 2,01 x 10-3 untuk M=4, 2,22 x 10-3 untuk M=8, dan 1,87 x 10-3 untuk M=16.

scholarly journals Pemodelan Non-uniform Coded-Modulation pada Kanal Akustik Bawah Air di Lingkungan Perairan Dangkal

2019 ◽  
Vol 9 (1) ◽  
pp. 38
Author(s):  
Sholihah Ayu Wulandari ◽  
Tri Budi Santoso ◽  
I Gede Puja Astawa ◽  
Muhamad Milchan
Keyword(s):  
Error Rate ◽  
Gaussian Noise ◽  
Signal To Noise Ratio ◽  
Additive White Gaussian Noise ◽  
Measurement Data ◽  
Coded Modulation ◽  
Bch Code ◽  
Ieee 802.11A ◽  
Shift Keying ◽  
Binary Information

In this paper, presented an OFDM performance evaluation with the Non-uniform Coded-Modulation in the underwater acoustic channel in shallow water. A row of binary information is encoded by BCH code (7.4) for error correction and combined with Non-uniform modulation which is the result of modification of the subcarrier arrangement of the OFDM standard IEEE 802.11a. Modeling uses 52 subcarriers consisting of 4 pilots and 48 subcarrier data which are divided into three parts, i.e.: 24 subcarrier data with 16-Quadrature Amplitude Modulation (16-QAM) modulation, 12 subcarrier data with Quadrature phase-shift keying (QPSK) modulation and 12 other data subcarriers with Binary key-shift keying (BPSK) modulation. The channel type used describes the Additive White Gaussian Noise (AWGN) condition and is the result of measurement data. The analysis is done in terms of Signal-to-Noise-Ratio (SNR) and Bit Error Rate (BER) show that the value of the error rate of 0.001, modulation of BPSK, QPSK, 16-QAM, and Non-uniform modulation required the power each 5 dB, 8.5 dB, 10.3 dB, and 7.9 dB. However, the proposed system is able to suppress the required power up to 6 dB. The proposed system also shows better performance than fixed modulation and Non-uniform Modulation, which in this case with low power to achieve the same error rate. In addition, the proposed system has a coding gain of 1.9 dB compared to a non-uniform modulation system. Real testing is also done with measurement data at Mangrove estuary, Surabaya. The results show performance similar to simulations performed on Gaussian noise channels.

scholarly journals Positioning Techniques in Indoor Environments Based on Stochastic Modeling of UWB Round Trip Time Measurements

2021 ◽  
Author(s):  
Paolo Carbone
Keyword(s):  
Particle Filter ◽  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Least Square ◽  
Indoor Environments ◽  
Round Trip Time ◽  
Round Trip ◽  
Positioning Systems ◽  
Trip Time ◽  
Non Gaussian

<div><div><div><p>In this paper, a technique for modeling propagation of Ultra Wide Band (UWB) signals in indoor or outdoor environments is proposed, supporting the design of a positioning systems based on Round Trip Time (RTT) measurements and on a particle filter. By assuming that nonlinear pulses are transmitted in an Additive White Gaussian Noise Channel, and detected using a threshold based receiver, it is shown that RTT measurements may be affected by a non-Gaussian noise. RTT noise properties are analyzed, and the effects of non-Gaussian noise on the performance of a RTT based positioning system are investigated. To this aim, a classical Least Square, an extended Kalman Filter and a Particle Filter are compared when used to detect a slowly moving target in presence of the modeled noise. It is shown that, in a realistic indoor environment, the Particle Filter solution may be a competitive solution, at a price of increased computational complexity. Experimental verifications validate the presented approach.</p></div></div></div>

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