Convolutional Coded Generalized Direct Sequence Spread Spectrum

In this thesis we investigate the worst-case performance of coded ordinary and coded generalized direct sequence spread spectrum (DSSS) systems in a communication channel corrupted by an unknown and arbitrary interfering signal of bounded power. We consider convolutional codes with Viterbi decoding in order to compare the performance of coded ordinary and coded generalized DSSS systems. For the generalized DSSS system, we use a pulse stream of +1,-1 and 0 as the spreading sequence, which is different from ordinary DSSS system which uses the typical sequence with pulse values of +1 and -1. A C program for performing Monte-Carlo simulations is written in order to evaluate and compare the performance of coded ordinary and coded generalized DSSS systems. Plots of the worst-case error probability versus signal-to-interference ratio are presented for different code rates and constraint lengths of the convolutional code. Simulation results of the worst-case performance of ordinary and generalized DSSS show that generalized DSSS consistently performs appreciably better than ordinary DSSS. Simulation is performed for various code rates, various constraint lengths of the convolutional code and various lengths of the convolutional interleaver. Over all these simulations, it is observed that the difference between ordinary and generalized DSSS gets more pronounced as the channel gets wors

DIGITAL VIDEO BROADCASTING VIA SATELLITE (DVB-S)

This paper provides a brief introduction to the DVB-S system based on [EN-300-421]. The DVB-S system provides directto-home (DTH) services for consumer integrated receiver decoders (IRD), as well as collective antenna systems (satellitemaster antenna television SMATV) and cable television head-end stations. The overview covers the physical layer thatcomprises adaptation, framing, coding, interleaving and modulation, and discusses error performance requirements toachieve quality of service (QoS) targets.Keywords: system provides direct-to-homey, satellite master antenna television and achieves quality of service

Convolutional Coded Generalized Direct Sequence Spread Spectrum

In this thesis we investigate the worst-case performance of coded ordinary and coded generalized direct sequence spread spectrum (DSSS) systems in a communication channel corrupted by an unknown and arbitrary interfering signal of bounded power. We consider convolutional codes with Viterbi decoding in order to compare the performance of coded ordinary and coded generalized DSSS systems. For the generalized DSSS system, we use a pulse stream of +1,-1 and 0 as the spreading sequence, which is different from ordinary DSSS system which uses the typical sequence with pulse values of +1 and -1. A C program for performing Monte-Carlo simulations is written in order to evaluate and compare the performance of coded ordinary and coded generalized DSSS systems. Plots of the worst-case error probability versus signal-to-interference ratio are presented for different code rates and constraint lengths of the convolutional code. Simulation results of the worst-case performance of ordinary and generalized DSSS show that generalized DSSS consistently performs appreciably better than ordinary DSSS. Simulation is performed for various code rates, various constraint lengths of the convolutional code and various lengths of the convolutional interleaver. Over all these simulations, it is observed that the difference between ordinary and generalized DSSS gets more pronounced as the channel gets wors

Feasibility study of 5G low-latency packet radio communications without preambles

This thesis deals with the feasibility of having lower latency for radio communication of short packets, which is the major traffic in the fifth generation (5G) of cellular systems. We will examine the possibility of using turbo synchronization instead of using a long preamble, which is needed for Data-Aided (DA) synchronization. The idea behind this is that short packets are required in low-latency applications. The overhead of preambles is very significant in case of short packets. Turbo synchronization allows to work with short or null preambles. The simulations will be run for a turbo synchronizer which has been implemented according to the Expectation Maximization (EM) formulation of the problem. The simulation results show that the implemented turbo synchronizer outperforms or attains the DA synchronizer in terms of reliability, accuracy and acquisition range for carrier phase synchronization. It means that the idea of eliminating the preamble from the short packet seems practical. The only downward is that there is a packet size limitation for the effective functionality of turbo synchronizer. Simulations indicate that the number of transmitted symbols should be higher than 128 coded symbols

Convolutional Coded Generalized Direct Sequence Spread Spectrum

In this thesis we investigate the worst-case performance of coded ordinary and coded generalized direct sequence spread spectrum (DSSS) systems in a communication channel corrupted by an unknown and arbitrary interfering signal of bounded power. We consider convolutional codes with Viterbi decoding in order to compare the performance of coded ordinary and coded generalized DSSS systems. For the generalized DSSS system, we use a pulse stream of +1,-1 and 0 as the spreading sequence, which is different from ordinary DSSS system which uses the typical sequence with pulse values of +1 and -1. A C program for performing Monte-Carlo simulations is written in order to evaluate and compare the performance of coded ordinary and coded generalized DSSS systems. Plots of the worst-case error probability versus signal-to-interference ratio are presented for different code rates and constraint lengths of the convolutional code. Simulation results of the worst-case performance of ordinary and generalized DSSS show that generalized DSSS consistently performs appreciably better than ordinary DSSS. Simulation is performed for various code rates, various constraint lengths of the convolutional code and various lengths of the convolutional interleaver. Over all these simulations, it is observed that the difference between ordinary and generalized DSSS gets more pronounced as the channel gets wors

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

Performance Evaluation of Wavelet-Coded OFDM on a 4.9 Gbps W-Band Radio-over-Fiber Link

Future generation mobile communications running on mm-wave frequencies will require great robustness against frequency selective channels. In this paper, we evaluate the transmission performance of 4.9 Gb/s wavelet-coded orthogonal frequency division multiplexing (OFDM) signals on a 10 km fiber plus 58 m wireless radio-over-fiber link using a mm-wave radio frequency carrier. The results show that a 2 × 128 wavelet-coded OFDM system achieves a bit-error rate of 1e-4 with nearly 2.5 dB less signal-to-noise ratio than a convolutional coded OFDM system with equivalent spectral efficiency for 8 GHz-wide signals with 512 subcarriers on a carrier frequency of 86 GHz. Our findings confirm the Tzannes’ theory that wavelet coding enables high diversity gains with a low complexity receiver and, most notably, without compromising the system’s spectral efficiency