135 research outputs found
New Identification and Decoding Techniques for Low-Density Parity-Check Codes
Error-correction coding schemes are indispensable for high-capacity high data-rate communication systems nowadays. Among various channel coding schemes, low-density parity-check (LDPC) codes introduced by pioneer Robert G. Gallager are prominent due to the capacity-approaching and superior error-correcting properties. There is no hard constraint on the code rate of LDPC codes. Consequently, it is ideal to incorporate LDPC codes with various code rate and codeword length in the adaptive modulation and coding (AMC) systems which change the encoder and the modulator adaptively to improve the system throughput. In conventional AMC systems, a dedicated control channel is assigned to coordinate the encoder/decoder changes. A questions then rises: if the AMC system still works when such a control channel is absent. This work gives positive answer to this question by investigating various scenarios consisting of different modulation schemes, such as quadrature-amplitude modulation (QAM), frequency-shift keying (FSK), and different channels, such as additive white Gaussian noise (AWGN) channels and fading channels. On the other hand, LDPC decoding is usually carried out by iterative belief-propagation (BP) algorithms. As LDPC codes become prevalent in advanced communication and storage systems, low-complexity LDPC decoding algorithms are favored in practical applications. In the conventional BP decoding algorithm, the stopping criterion is to check if all the parities are satisfied. This single rule may not be able to identify the undecodable blocks, as a result, the decoding time and power consumption are wasted for executing unnecessary iterations. In this work, we propose a new stopping criterion to identify the undecodable blocks in the early stage of the iterative decoding process. Furthermore, in the conventional BP decoding algorithm, the variable (check) nodes are updated in parallel. It is known that the number of iterations can be reduced by the serial scheduling algorithm. The informed dynamic scheduling (IDS) algorithms were proposed in the existing literatures to further reduce the number of iterations. However, the computational complexity involved in finding the update node in the existing IDS algorithms would not be neglected. In this work, we propose a new efficient IDS scheme which can provide better performance-complexity trade-off compared to the existing IDS ones. In addition, the iterative decoding threshold, which is used for differentiating which LDPC code is better, is investigated in this work. A family of LDPC codes, called LDPC convolutional codes, has drawn a lot of attentions from researchers in recent years due to the threshold saturation phenomenon. The IDT for an LDPC convolutional code may be computationally demanding when the termination length goes to thousand or even approaches infinity, especially for AWGN channels. In this work, we propose a fast IDT estimation algorithm which can greatly reduce the complexity of the IDT calculation for LDPC convolutional codes with arbitrary large termination length (including infinity). By utilizing our new IDT estimation algorithm, the IDTs for LDPC convolutional codes with arbitrary large termination length (including infinity) can be quickly obtained
Blind LDPC encoder identification
Nowadays, adaptive modulation and coding (AMC) techniques can facilitate flexible strategies subject to dynamic channel quality. The AMC transceivers select the most suitable coding and modulation mechanisms subject to the acquired channel information. Meanwhile, a control channel or a preamble is usually required to synchronously coordinate such changes between transmitters and receivers. On the other hand, low-density parity-check (LDPC) codes become more and more popular in recent years due to their promising capacity-approaching property. The broad range of variations in code rates and codeword lengths for LDPC codes makes them ideal candidates for future AMC transceivers. The blind encoder identification problem emerges when the underlying control channel is absent or the preamble is not allowed in AMC systems. It would be quite intriguing for one to build a blind encoder identification technique without spectrum-efficiency sacrifice. Therefore, in this thesis, we investigate blind LDPC encoder identification for AMC systems. Specifically, we would like to tackle the blind identification of binary LDPC codes (encoders) for binary phase-shift keying (BPSK) signals and nonbinary LDPC codes for quadrature-amplitude modulation (QAM) signals. We propose a novel blind identification system which consists of three major components, namely expectation-maximization (EM) estimator for unknown parameters (signal amplitude, noise variance, and phase offset), log-likelihood ratio (LLR) estimator for syndrome a posteriori probabilities, and maximum average-LLR detector. Monte Carlo simulation results demonstrate that our proposed blind LDPC encoder identification scheme is very promising over different signal-to-noise ratio conditions
Coded DS-CDMA Systems with Iterative Channel Estimation and no Pilot Symbols
In this paper, we describe direct-sequence code-division multiple-access
(DS-CDMA) systems with quadriphase-shift keying in which channel estimation,
coherent demodulation, and decoding are iteratively performed without the use
of any training or pilot symbols. An expectation-maximization
channel-estimation algorithm for the fading amplitude, phase, and the
interference power spectral density (PSD) due to the combined interference and
thermal noise is proposed for DS-CDMA systems with irregular repeat-accumulate
codes. After initial estimates of the fading amplitude, phase, and interference
PSD are obtained from the received symbols, subsequent values of these
parameters are iteratively updated by using the soft feedback from the channel
decoder. The updated estimates are combined with the received symbols and
iteratively passed to the decoder. The elimination of pilot symbols simplifies
the system design and allows either an enhanced information throughput, an
improved bit error rate, or greater spectral efficiency. The interference-PSD
estimation enables DS-CDMA systems to significantly suppress interference.Comment: To appear, IEEE Transactions on Wireless Communication
Secured Audio Signal Transmission in 5G Compatible mmWave Massive MIMO FBMC System with Implementation of Audio-to-image Transformation Aided Encryption Scheme
In this paper, we have made comprehensive study for the performance evaluation of mmWave massive MIMO FBMC wireless communication system. The 165F2;56 large MIMO antenna configured simulated system under investigation incorporates three modern channel coding (Turbo, LDPC and (3, 2) SPC, higher order digital modulation (256-QAM)) and various signal detection (Q-Less QR, Lattice Reduction(LR) based Zero-forcing(ZF), Lattice Reduction (LR) based ZF-SIC and Complex-valued LLL(CLLL) algorithm implemented ZF-SIC) schemes. An audio to image conversion aided chaos-based physical layer security scheme has also been implemented in such study. On considering transmission of encrypted audio signal in a hostile fading channel, it is noticeable from MATLAB based simulation study that the LDPC Channel encoded system is very much robust and effective in retrieving color image under utilization of Lattice Reduction(LR) based ZF-SIC signal detection and 16- QAM digital modulation techniques
Simulation framework for multigigabit applications at 60 GHz
This dissertation describes the implementation of a OFDM-based simulation framework
for multigigabit applications at 60 GHz band over indoor multipath fading channels.
The main goal of the framework is to provide a modular simulation tool designed
for high data rate application in order to be easily adapted to a speci c standard or
technology, such as 5G. The performance of OFDM using mmWave signals is severely
a ected by non-linearities of the RF front-ends. This work analyses the impact of RF
impairments in an OFDM system over multipath fading channels at 60 GHz using the
proposed simulation framework. The impact of those impairments is evaluated through
the metrics of BER, CFR, operation range and PSNR for residential and kiosk scenarios,
suggested by the standard for LOS and NLOS. The presented framework allows
the employment of 16 QAM or 64 QAM modulation scheme, and the length of the
cyclic pre x extension is also con gurable. In order to simulate a realistic multipath
fading channel, the proposed framework allows the insertion of a channel impulse response
de ned by the user. The channel estimation can be performed either using
pilot subcarriers or Golay sequence as channel estimation sequences. Independently of
the channel estimation technique selected, frequency domain equalization is available
through ZF approach or MMSE. The simulation framework also allows channel coding
techniques in order to provide a more robustness transmission and to improve the link
budget
Advanced Statistical Signal Processing Methods in Sensing, Detection, and Estimation for Communication Applications
The applications of wireless communications and digital signal processing have dramatically changed the way we live, work, and learn over decades. The requirement of higher throughput and ubiquitous connectivity for wireless communication systems has become prevalent nowadays. Signal sensing, detection and estimation have been prevalent in signal processing and communications for many years. The relevant studies deal with the processing of information-bearing signals for the purpose of information extraction. Nevertheless, new robust and efficient signal sensing, detection and estimation techniques are still in demand since there emerge more and more practical applications which rely on them. In this dissertation work, we proposed several novel signal sensing, detection and estimation schemes for wireless communications applications, such as spectrum sensing, symbol-detection/channel-estimation, and encoder identification. The associated theories and practice in robustness, computational complexity, and overall system performance evaluation are also provided
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