300 research outputs found
Computationally-efficient iterative demodulation of coded PSK signals affected by phase noise
This paper considers two recently-proposed receivers, Tikh and DCT. Both receivers are computationally-efficient, iterative and designed to be robust against phase noise on the local oscillators of digital bandpass communication systems. The presented results build on our prior research. We discuss the initialization of the DCT receiver, explore reducing the computational complexity by simplifying the receiver scheduling and study the effect of a small frequency offset. Coded PSK signaling and additive white Gaussian noise are assumed
Performance of Turbo Coded OFDM in Wireless Application
Orthogonal Frequency Division Multiplexing (OFDM) has become a popular
modulation method in high speed wireless communications. By partitioning a wideband
fading channel into flat narrowband channels, OFDM is able to mitigate the detrimental
effects of multi path fading using a simple one- tap equalizer. There is a growing need to
quickly transmit information wirelessly and accurately.
Engineers have already combine techniques such as OFDM suitable for high data rate
transmission with forward error correction (FEC) methods over wireless channels. In this
thesis, we enhance the system throughput of a working OFDM system by adding turbo
coding. The smart use of coding and power allocation in OFDM will be useful to the desired
performance at higher data rates.
Error control codes have become a vital part of modern digital wireless systems,
enabling reliable transmission to be achieved over noisy channels. Over the past decade,
turbo codes have been widely considered to be the most powerful error control code of
practical importance. In the same time-scale, mixed voice/data networks have advanced
further and the concept of global wireless networks and terrestrial links has emerged. Such
networks present the challenge of optimizing error control codes for different channel types,
and for the different qualities of service demanded by voice and data
Performance analysis of turbo coded OFDM in wireless application
Orthogonal Frequency Division Multiplexing (OFDM) has become a popular modulation method in high speed wireless communications. By partitioning a wideband fading channel into flat narrowband channels, OFDM is able to mitigate the detrimental effects of multi path fading using a simple one- tap equalizer. There is a growing need to quickly transmit information wirelessly and accurately.Engineers have already combine techniques such as OFDM suitable for high data rate transmission with forward error correction (FEC) methods over wireless channels. In this thesis, we enhance the system throughput of a working OFDM system by adding turbo coding. The smart use of coding and power allocation in OFDM will be useful to the desired performance at higher data rates.Error control codes have become a vital part of modern digital wireless systems,enabling reliable transmission to be achieved over noisy channels. Over the past decade,turbo codes have been widely considered to be the most powerful error control code of practical importance. In the same time-scale, mixed voice/data networks have advanced further and the concept of global wireless networks and terrestrial links has emerged. Such networks present the challenge of optimizing error control codes for different channel types,and for the different qualities of service demanded by voice and data
Signal mapping designs for bit-interleaved coded modulation with iterative decoding (BICM-ID)
Bit-interleaved coded modulation with iterative decoding (BICM-ID)is a spectral efficient coded modulation technique to improve the performance of digital communication systems. It has been widely known that for fixed signal constellation, interleaver and error control code, signal mapping plays an important role in
determining the error performance of a BICM-ID system. This thesis concentrates on signal mapping designs for BICM-ID systems. To this end, the distance criteria to find the best mapping in terms of the asymptotic performance are first analytically derived for different channel models. Such criteria are then used to find good mappings for various two-dimensional
8-ary constellations. The usefulness of the proposed mappings of 8-ary constellations is verified by both the error floor bound and simulation results.
Moreover, new mappings are also proposed for BICM-ID systems employing the quadrature phase shift keying (QPSK) constellation. The new mappings are obtained by considering many QPSK symbols over a multiple symbol interval, which essentially creates hypercube constellations. Analytical and simulation results show that the use of the proposed
mappings together with very simple convolutional codes can offer significant coding gains over the conventional BICM-ID systems for all the channel models considered. Such coding gains are
achieved without any bandwidth nor power expansion and with a very small increase in the system complexity
Capacity -based parameter optimization of bandwidth constrained CPM
Continuous phase modulation (CPM) is an attractive modulation choice for bandwidth limited systems due to its small side lobes, fast spectral decay and the ability to be noncoherently detected. Furthermore, the constant envelope property of CPM permits highly power efficient amplification. The design of bit-interleaved coded continuous phase modulation is characterized by the code rate, modulation order, modulation index, and pulse shape. This dissertation outlines a methodology for determining the optimal values of these parameters under bandwidth and receiver complexity constraints. The cost function used to drive the optimization is the information-theoretic minimum ratio of energy-per-bit to noise-spectral density found by evaluating the constrained channel capacity. The capacity can be reliably estimated using Monte Carlo integration. A search for optimal parameters is conducted over a range of coded CPM parameters, bandwidth efficiencies, and channels. Results are presented for a system employing a trellis-based coherent detector. To constrain complexity and allow any modulation index to be considered, a soft output differential phase detector has also been developed.;Building upon the capacity results, extrinsic information transfer (EXIT) charts are used to analyze a system that iterates between demodulation and decoding. Convergence thresholds are determined for the iterative system for different outer convolutional codes, alphabet sizes, modulation indices and constellation mappings. These are used to identify the code and modulation parameters with the best energy efficiency at different spectral efficiencies for the AWGN channel. Finally, bit error rate curves are presented to corroborate the capacity and EXIT chart designs
Machine Learning Techniques to Mitigate Nonlinear Phase Noise in Moderate Baud Rate Optical Communication Systems
Nonlinear phase noise (NLPN) is the most common impairment that degrades the performance of radio-over-fiber networks. The effect of NLPN in the constellation diagram consists of a shape distortion of symbols that increases the symbol error rate due to symbol overlapping when using a conventional demodulation grid. Symbol shape characterization was obtained experimentally at a moderate baud rate (250 MBd) for constellations impaired by phase noise due to a mismatch between the optical carrier and the transmitted radio frequency signal. Machine learning algorithms have become a powerful tool to perform monitoring and to identify and mitigate distortions introduced in both the electrical and optical domains. Clustering-based demodulation assisted with Voronoi contours enables the definition of non-Gaussian boundaries to provide flexible demodulation of 16-QAM and 4+12 PSK modulation formats. Phase-offset and in-phase and quadrature imbalance may be detected on the received constellation and compensated by applying thresholding boundaries obtained from impairment characterization through statistical analysis. Experimental results show increased tolerance to the optical signal-to-noise ratio (OSNR) obtained from clustering methods based on k-means and fuzzy c-means Gustafson-Kessel algorithms. Improvements of 3.2 dB for 16-QAM, and 1.4 dB for 4+12 PSK in the OSNR scale as a function of the bit error rate are obtained without requiring additional compensation algorithms
Machine Learning Techniques to Mitigate Nonlinear Phase Noise in Moderate Baud Rate Optical Communication Systems
Nonlinear phase noise (NLPN) is the most common impairment that degrades the performance of radio-over-fiber networks. The effect of NLPN in the constellation diagram consists of a shape distortion of symbols that increases the symbol error rate due to symbol overlapping when using a conventional demodulation grid. Symbol shape characterization was obtained experimentally at a moderate baud rate (250 MBd) for constellations impaired by phase noise due to a mismatch between the optical carrier and the transmitted radio frequency signal. Machine learning algorithms have become a powerful tool to perform monitoring and to identify and mitigate distortions introduced in both the electrical and optical domains. Clustering-based demodulation assisted with Voronoi contours enables the definition of non-Gaussian boundaries to provide flexible demodulation of 16-QAM and 4+12 PSK modulation formats. Phase-offset and in-phase and quadrature imbalance may be detected on the received constellation and compensated by applying thresholding boundaries obtained from impairment characterization through statistical analysis. Experimental results show increased tolerance to the optical signal-to-noise ratio (OSNR) obtained from clustering methods based on k-means and fuzzy c-means Gustafson-Kessel algorithms. Improvements of 3.2 dB for 16-QAM, and 1.4 dB for 4+12 PSK in the OSNR scale as a function of the bit error rate are obtained without requiring additional compensation algorithms
Chapter Machine Learning Techniques to Mitigate Nonlinear Phase Noise in Moderate Baud Rate Optical Communication Systems
Nonlinear phase noise (NLPN) is the most common impairment that degrades the performance of radio-over-fiber networks. The effect of NLPN in the constellation diagram consists of a shape distortion of symbols that increases the symbol error rate due to symbol overlapping when using a conventional demodulation grid. Symbol shape characterization was obtained experimentally at a moderate baud rate (250 MBd) for constellations impaired by phase noise due to a mismatch between the optical carrier and the transmitted radio frequency signal. Machine learning algorithms have become a powerful tool to perform monitoring and to identify and mitigate distortions introduced in both the electrical and optical domains. Clustering-based demodulation assisted with Voronoi contours enables the definition of non-Gaussian boundaries to provide flexible demodulation of 16-QAM and 4+12 PSK modulation formats. Phase-offset and in-phase and quadrature imbalance may be detected on the received constellation and compensated by applying thresholding boundaries obtained from impairment characterization through statistical analysis. Experimental results show increased tolerance to the optical signal-to-noise ratio (OSNR) obtained from clustering methods based on k-means and fuzzy c-means Gustafson-Kessel algorithms. Improvements of 3.2 dB for 16-QAM, and 1.4 dB for 4+12 PSK in the OSNR scale as a function of the bit error rate are obtained without requiring additional compensation algorithms
Development of an acoustic communication link for micro underwater vehicles
PhD ThesisIn recent years there has been an increasing trend towards the use of
Micro Remotely Operated Vehicles (μROVs), such as the Videoray and
Seabotix LBV products, for a range of subsea applications, including
environmental monitoring, harbour security, military surveillance and
offshore inspection. A major operational limitation is the umbilical cable,
which is traditionally used to supply power and communications to the
vehicle. This tether has often been found to significantly restrict the
agility of the vehicle or in extreme cases, result in entanglement with
subsea structures.
This thesis addresses the challenges associated with developing a reliable
full-duplex wireless communications link aimed at tetherless operation
of a μROV. Previous research has demonstrated the ability to
support highly compressed video transmissions over several kilometres
through shallow water channels with large range-depth ratios. However,
the physical constraints of these platforms paired with the system cost
requirements pose significant additional challenges.
Firstly, the physical size/weight of transducers for the LF (8-16kHz)
and MF (16-32kHz) bands would significantly affect the dynamics of the
vehicle measuring less than 0.5m long. Therefore, this thesis explores the
challenges associated with moving the operating frequency up to around
50kHz centre, along with the opportunities for increased data rate and
tracking due to higher bandwidth.
The typical operating radius of μROVs is less than 200m, in water
< 100m deep, which gives rise to multipath channels characterised by
long timespread and relatively sparse arrivals. Hence, the system must
be optimised for performance in these conditions. The hardware costs of
large multi-element receiver arrays are prohibitive when compared to the
cost of the μROV platform. Additionally, the physical size of such arrays
complicates deployment from small surface vessels. Although some
recent developments in iterative equalisation and decoding structures
have enhanced the performance of single element receivers, they are not
found to be adequate in such channels. This work explores the optimum
cost/performance trade-off in a combination of a micro beamforming array
using a Bit Interleaved Coded Modulation with Iterative Decoding
(BICM-ID) receiver structure.
The highly dynamic nature of μROVs, with rapid acceleration/deceleration
and complex thruster/wake effects, are also a significant challenge to reliable
continuous communications. The thesis also explores how these effects
can best be mitigated via advanced Doppler correction techniques,
and adaptive coding and modulation via a simultaneous frequency multiplexed
down link. In order to fully explore continuous adaptation of
the transmitted signals, a real-time full-duplex communication system
was constructed in hardware, utilising low cost components and a highly
optimised PC based receiver structure. Rigorous testing, both in laboratory
conditions and through extensive field trials, have enabled the
author to explore the performance of the communication link on a vehicle
carrying out typical operations and presenting a wide range of channel,
noise, Doppler and transmission latency conditions. This has led to a
comprehensive set of design recommendations for a reliable and cost effective
link capable of continuous throughputs of >30 kbits/s
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