Iterative decoding combined with physical-layer network coding on impulsive noise channels

PhD ThesisThis thesis investigates the performance of a two-way wireless relay channel (TWRC) employing physical layer network coding (PNC) combined with binary and non-binary error-correcting codes on additive impulsive noise channels. This is a research topic that has received little attention in the research community, but promises to offer very interesting results as well as improved performance over other schemes. The binary channel coding schemes include convolutional codes, turbo codes and trellis bitinterleaved coded modulation with iterative decoding (BICM-ID). Convolutional codes and turbo codes defined in finite fields are also covered due to non-binary channel coding schemes, which is a sparse research area. The impulsive noise channel is based on the well-known Gaussian Mixture Model, which has a mixture constant denoted by α. The performance of PNC combined with the different coding schemes are evaluated with simulation results and verified through the derivation of union bounds for the theoretical bit-error rate (BER). The analyses of the binary iterative codes are presented in the form of extrinsic information transfer (ExIT) charts, which show the behaviour of the iterative decoding algorithms at the relay of a TWRC employing PNC and also the signal-to-noise ratios (SNRs) when the performance converges. It is observed that the non-binary coding schemes outperform the binary coding schemes at low SNRs and then converge at higher SNRs. The coding gain at low SNRs become more significant as the level of impulsiveness increases. It is also observed that the error floor due to the impulsive noise is consistently lower for non-binary codes. There is still great scope for further research into non-binary codes and PNC on different channels, but the results in this thesis have shown that these codes can achieve significant coding gains over binary codes for wireless networks employing PNC, particularly when the channels are harsh

Investigation of non-binary trellis codes designed for impulsive noise environments

PhD ThesisIt is well known that binary codes with iterative decoders can achieve near Shannon limit performance on the additive white Gaussian noise (AWGN) channel, but their performance on more realistic wired or wireless channels can become degraded due to the presence of burst errors or impulsive noise. In such extreme environments, error correction alone cannot combat the serious e ect of the channel and must be combined with the signal processing techniques such as channel estimation, channel equalisation and orthogonal frequency division multiplexing (OFDM). However, even after the received signal has been processed, it can still contain burst errors, or the noise present in the signal maybe non Gaussian. In these cases, popular binary coding schemes such as Low-Density Parity-Check (LDPC) or turbo codes may not perform optimally, resulting in the degradation of performance. Nevertheless, there is still scope for the design of new non-binary codes that are more suitable for these environments, allowing us to achieve further gains in performance. In this thesis, an investigation into good non-binary trellis error-correcting codes and advanced noise reduction techniques has been carried out with the aim of enhancing the performance of wired and wireless communication networks in di erent extreme environments. These environments include, urban, indoor, pedestrian, underwater, and powerline communication (PLC). This work includes an examination of the performance of non-binary trellis codes in harsh scenarios such as underwater communications when the noise channel is additive S S noise. Similar work was also conducted for single input single output (SISO) power line communication systems for single carrier (SC) and multi carrier (MC) over realistic multi-path frequency selective channels. A further examination of multi-input multi-output (MIMO) wired and wireless systems on Middleton class A noise channel was carried out. The main focus of the project was non-binary coding schemes as it is well-known that they outperform their binary counterparts when the channel is bursty. However, few studies have investigated non-binary codes for other environments. The major novelty of this work is the comparison of the performance of non-binary trellis codes with binary trellis codes in various scenarios, leading to the conclusion that non-binary codes are, in most cases, superior in performance to binary codes. Furthermore, the theoretical bounds of SISO and MIMO binary and non-binary convolutional coded OFDM-PLC systems have been investigated for the rst time. In order to validate our results, the implementation of simulated and theoretical results have been obtained for di erent values of noise parameters and on di erent PLC channels. The results show a strong agreement between the simulated and theoretical analysis for all cases.University of Thi-Qar for choosing me for their PhD scholarship and the Iraqi Ministry of Higher Education and Scienti c Research (MOHESR) for granting me the funds to study in UK. In addition, there was ample support towards my stay in the UK from the Iraqi Cultural Attach e in Londo

Channel Parameters Estimation Algorithm Based on The Characteristic Function under Impulse Noise Environment

Under communication environments, such as wireless sensor networks, the noise observed usually exhibits impulsive as well as Gaussian characteristics. In the initialization of channel iterative decoder, such as low density parity check codes, it is required in advance to estimate the channel parameters to obtain the prior information from the received signals. In this paper, a blind channel parameters estimator under impulsive noise environment is proposed, which is based on the empirical characteristic function in MPSK/MQAM higher-order modulation system. Simulation results show that for various MPSK/MQAM modulations, the estimator can obtain a more accurate unbiased estimation even though we do not know which kind of higher-order modulation is used

Advanced Coding And Modulation For Ultra-wideband And Impulsive Noises

The ever-growing demand for higher quality and faster multimedia content delivery over short distances in home environments drives the quest for higher data rates in wireless personal area networks (WPANs). One of the candidate IEEE 802.15.3a WPAN proposals support data rates up to 480 Mbps by using punctured convolutional codes with quadrature phase shift keying (QPSK) modulation for a multi-band orthogonal frequency-division multiplexing (MB-OFDM) system over ultra wideband (UWB) channels. In the first part of this dissertation, we combine more powerful near-Shannon-limit turbo codes with bandwidth efficient trellis coded modulation, i.e., turbo trellis coded modulation (TTCM), to further improve the data rates up to 1.2 Gbps. A modified iterative decoder for this TTCM coded MB-OFDM system is proposed and its bit error rate performance under various impulsive noises over both Gaussian and UWB channel is extensively investigated, especially in mismatched scenarios. A robust decoder which is immune to noise mismatch is provided based on comparison of impulsive noises in time domain and frequency domain. The accurate estimation of the dynamic noise model could be very difficult or impossible at the receiver, thus a significant performance degradation may occur due to noise mismatch. In the second part of this dissertation, we prove that the minimax decoder in \cite, which instead of minimizing the average bit error probability aims at minimizing the worst bit error probability, is optimal and robust to certain noise model with unknown prior probabilities in two and higher dimensions. Besides turbo codes, another kind of error correcting codes which approach the Shannon capacity is low-density parity-check (LDPC) codes. In the last part of this dissertation, we extend the density evolution method for sum-product decoding using mismatched noises. We will prove that as long as the true noise type and the estimated noise type used in the decoder are both binary-input memoryless output symmetric channels, the output from mismatched log-likelihood ratio (LLR) computation is also symmetric. We will show the Shannon capacity can be evaluated for mismatched LLR computation and it can be reduced if the mismatched LLR computation is not an one-to-one mapping function. We will derive the Shannon capacity, threshold and stable condition of LDPC codes for mismatched BIAWGN and BIL noise types. The results show that the noise variance estimation errors will not affect the Shannon capacity and stable condition, but the errors do reduce the threshold. The mismatch in noise type will only reduce Shannon capacity when LLR computation is based on BIL

Coded modulation techniques with bit interleaving and iterative processing for impulsive noise channels

Power line communications (PLC) surfers performance degradation due mainly to impulsive noise interference generated by electrical appliances. This thesis studies coded modulation techniques to improve the spectral efficiency and error performance of PLC. Considered in the first part is the application of bit-interleaved coded modulation with iterative decoding (BICM-ID) in class-A impulsive noise environment. In particular, the optimal soft-output demodulator and its suboptimal version are presented for an additive class-A noise (AWAN) channel so that iterative demodulation and decoding can be performed at the receiver. The effect of signal mapping on the error performance of BICM-ID systems in impulsive noise is then investigated, with both computer simulations and a tight error bound on the asymptotic performance. Extrinsic information transfer (EXIT) chart analysis is performed to illustrate the convergence properties of different mappings. The superior performance of BICMID compared to orthogonal frequency-division multiplexing (OFDM) is also clearly demonstrated.Motivated by the successes of both BICM-ID and OFDM in improving the error performance of communications systems in impulsive noise environment, the second part of this thesis introduces a novel scheme of bit-interleaved coded OFDM with iterative decoding (BI-COFDM-ID) over the class-A impulsive noise channel. Here, an iterative receiver composed of outer and inner iteration loops is first described in detail. Error performance improvements of the proposed iterative receiver with different iteration strategies are presented and discussed. Performance comparisons of BI-COFDM-ID, BICM-ID and iteratively decoded OFDM are made to illustrate the superiority of BI-COFDM-ID. The effect of signal mapping on the error performance of BI-COFDM-ID is also studied

Low Complexity Rate Compatible Puncturing Patterns Design for LDPC Codes

In contemporary digital communications design, two major challenges should be addressed: adaptability and flexibility. The system should be capable of flexible and efficient use of all available spectrums and should be adaptable to provide efficient support for the diverse set of service characteristics. These needs imply the necessity of limit-achieving and flexible channel coding techniques, to improve system reliability. Low Density Parity Check (LDPC) codes fit such requirements well, since they are capacity-achieving. Moreover, through puncturing, allowing the adaption of the coding rate to different channel conditions with a single encoder/decoder pair, adaptability and flexibility can be obtained at a low computational cost.In this paper, the design of rate-compatible puncturing patterns for LDPCs is addressed. We use a previously defined formal analysis of a class of punctured LDPC codes through their equivalent parity check matrices. We address a new design criterion for the puncturing patterns using a simplified analysis of the decoding belief propagation algorithm, i.e., considering a Gaussian approximation for message densities under density evolution, and a simple algorithmic method, recently defined by the Authors, to estimate the threshold for regular and irregular LDPC codes on memoryless binary-input continuous-output Additive White Gaussian Noise (AWGN) channels

SOVA decoding in symmetric alpha-stable noise

Soft-Output Viterbi Algorithm (SOVA) is one type of recovery memory-less Markov Chain and is used widely to decode convolutional codes. Fundamentally, conventional SOVA is designed on the basis of Maximum A-Posteriori Probability (APP) with the assumption of normal distribution. Therefore, conventional SOVA fails miserably in the presence of symmetric alpha stable noise S\ensuremathα S which is one form of stable random processes widely accepted for impulsive noise modeling. The author studies and has improved the performance of conventional SOVA by introducing Cauchy function into path-metric calculation. Substantial performance improvement was gained from Mento Carlo Simulation for SOVA based turbo codes