scholarly journals Técnicas para la implementación de turbo decodificadores con baja latencia

2019 ◽  
pp. 29-41
Author(s):  
Lennin Conrado Yllescas-Calderon ◽  
Ramón Parra-Michel ◽  
Luis F Gonzalez-Pérez
Keyword(s):  
Channel Coding ◽  
Iterative Decoding ◽  
Turbo Coding ◽  
Processing Capacity ◽  
Turbo Decoding ◽  
Turbo Decoder ◽  
Transmission Rates ◽  
Communications Systems ◽  
Lte Advanced ◽  
Turbo Decoders

Turbo coding is a channel coding technique that increases the capacity of communications systems, especially wireless and mobile. Due to its high correction capability, this technique is used in modern wireless communication standards such as 3GPP and LTE/LTE-Advanced. One of the features of these systems is the increase in data processing capacity, where transmission rates of up to 1 Gbps are specified. However, the turbo coding technique inherently presents a limited performance as a consequence of the turbo decoding process at the reception stage. The turbo decoder presents a high operation latency mainly caused by the iterative decoding process, the interleaver and deinterleaver stage and the estimation process of the information bits. In this work, we show the techniques used to implement modern low-latency turbo decoders suitable for 3G and 4G standards.

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 Analysis of iteration control for turbo decoders in turbo synchronization applications

2009 ◽  
Vol 7 ◽  
pp. 139-144
Author(s):  
T. Lehnigk-Emden ◽  
U. Wasenmüller ◽  
C. Gimmler ◽  
N. Wehn
Keyword(s):  
Turbo Codes ◽  
Channel Coding ◽  
Communication Systems ◽  
Wireless Data ◽  
Turbo Decoder ◽  
Wireless Data Transmission ◽  
Turbo Decoders ◽  
Xilinx Fpga ◽  
Digital Communication Systems ◽  
Turbo Synchronization

Abstract. Wireless data transmission results in frequency and phase offsets of the signal in the receiver. In addition, the received symbols are corrupted by noise. Therefore, synchronization and channel coding are vital parts of each receiver in digital communication systems. By combining the phase and frequency synchronization with an advanced iterative channel decoder (inner loop) e.g. turbo codes in an iterative way (outer loop), the communications performance can be further increased. This principle is referred to as turbo synchronization. The energy consumption and the peak throughput of the system depend on the number of iterations for both loops. An advanced iteration control can decrease the mean number of needed iterations by detecting correctly decoded blocks. This leads to a dramatic energy saving or to an increase of throughput. In this paper we present a new stopping criterion for decodable blocks for turbo decoding in interrelation with turbo synchronization. Furthermore the implementation complexity of the turbo decoder is shown on a Xilinx FPGA.

scholarly journals CCSDS telemetry channel coding: the turbo coding option

1998 ◽  
Author(s):  
G.-P. Calzolari ◽  
E. Vassallo ◽  
S. Habinc
Keyword(s):  
Channel Coding ◽  
Turbo Coding

scholarly journals Higher performance and lower complexity turbo decoding scheme for 4G-LTE using unpunctured turbo trellis-coded modulation

2020 ◽  
Vol 18 (1) ◽  
pp. 351
Author(s):  
Elarbi Abderraouf ◽  
Abdesselam Bassou ◽  
Mohamed Rida Lahcene Rida Lahcene
Keyword(s):  
Mobile Networks ◽  
Channel Coding ◽  
Iterative Decoding ◽  
High Efficiency ◽  
Turbo Code ◽  
Mobile Network ◽  
Coded Modulation ◽  
Mobile Technologies ◽  
Trellis Coded Modulation ◽  
Trellis Coded

<p>Thanks to the success of smart phones and mobile-ready laptops, data traffic has recently grown exponentially, and the demand for mobile data has risen very dramatically. These requests in large capacity can only be satisfied by a high efficiency and a very good optimization of the infrastructures of the mobile networks, while taking into account the constraints which are the power, bandwidth and a limited complexity. The task of developing mobile technologies has also evolved from a national or regional focus to a complex and growing mission, supported by global standards development organizations such as 3GPP (3rd Group Partnership Project). Through this research, we present everything related to the simulation of the 4G mobile network system (LTE), which can provide high data flow with good quality, through three model channels known as (EPA, EVA, ETU). In this work we focus on the block ‘iterative decoding channel encoder’ in the LTE system, where the iterative channel coding called ‘Turbo-code’ (TC) is substituted by the iterative coding channel called ‘Unpunctured Turbo Trellis-coded Modulation’ (UTTCM). The simulation results showed that with less decoding complexities, UTTCM's LTE system gives good performance (in terms of BER).</p>

Efficient highly-parallel turbo decoder for 3GPP LTE-Advanced

2015 ◽  
Author(s):  
Jing-Shiun Lin ◽  
Ming-Der Shieh ◽  
Chung-Yen Liu ◽  
Der-Wei Yang
Keyword(s):  
Turbo Decoder ◽  
3Gpp Lte ◽  
Lte Advanced

scholarly journals Software implementation of LTE-advanced using Matlab Simulink

2017 ◽  
Vol 6 (4) ◽  
pp. 116 ◽  
Author(s):  
Wessam Mostafa ◽  
Eman Mohamed ◽  
Abdelhalim Zekry
Keyword(s):  
Digital Signal Processor ◽  
Channel Coding ◽  
Signal To Noise Ratio ◽  
Digital Signal ◽  
International Telecommunication Union ◽  
Matlab Simulink ◽  
International Telecommunication ◽  
Coding Schemes ◽  
Simulink Model ◽  
Lte Advanced

Long Term Evolution Advanced (LTE-A) is the evolution of the LTE that developed by 3rd Generation Partnership Project (3GPP).LTE-A exceeded International Telecommunication Union (ITU) requirements for 4th Generation (4G) known as International Mobile Telecommunications (IMT-Advanced). It is formally introduced in October 2009. This paper presents a study and an implementation of the LTE-A downlink physical layer based on 3GPP release 10 standards using Matlab simulink. In addition, it provides the LTE-A performance in terms of Bit Error Rate (BER) against Signal to Noise Ratio (SNR) for different modulation and channel coding schemes. Moreover, different scenarios of Carrier Aggregation (CA) are modeled and implemented. The Simulink model developed for the LTE-A transceiver can be translated into digital signal processor DSP code or VHDL on FPGA code.

Reverse Rate Matching for Low-Power LTE-Advanced Turbo Decoders

2015 ◽  
Vol 62 (12) ◽  
pp. 2920-2928 ◽  
Author(s):  
Injae Yoo ◽  
Bongjin Kim ◽  
In-Cheol Park
Keyword(s):  
Low Power ◽  
Lte Advanced ◽  
Turbo Decoders

scholarly journals Turbo Decoder for Low-Power Ultrawideband Communication Systems

2008 ◽  
Vol 2008 ◽  
pp. 1-7 ◽  
Author(s):  
Esam A. Obiedat ◽  
Lei Cao
Keyword(s):  
Computational Complexity ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Signal To Noise Ratio ◽  
Turbo Decoding ◽  
Ofdm Symbol ◽  
Turbo Decoder ◽  
Multicarrier Systems ◽  
Ultrawideband Communication ◽  
Ber Performance

A new method to reduce the computational complexity of the turbo decoding in ultrawideband (UWB) orthogonal frequency division multiplexing (OFDM) system is proposed. Existing stopping techniques for turbo decoding process using constrained decoding assume fixed signal-to-noise ratio (SNR) for all the OFDM symbol bits so they fail to yield an acceptable bit-error rate (BER) performance in multicarrier systems. In this paper, we propose a bit-level stopping technique for turbo decoding process based on the constrained decoding method. In this technique, we combine the cyclic redundancy check (CRC) with an adaptive threshold on the log likelihood ratio (LLR) on each subcarrier to detect for convergence. The threshold is adaptive in the sense that the threshold on the LLR of a bit is determined by the average SNR of the OFDM symbol and the channel gain of the transmission subcarrier. Results show that when the channel state information (CSI) is used to determine the threshold on LLR, the stopping technique can reduce the computational complexity by about 0.5–2.5 equivalent iterations compared to GENIE turbo without degradation in the BER performance.

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