1,067 research outputs found
Low-Density Parity-Check Coded High-order Modulation Schemes
In this thesis, we investigate how to support reliable data transmissions at high speeds in future communication systems, such as 5G/6G, WiFi, satellite, and optical communications. One of the most fundamental problems in these communication systems is how to reliably transmit information with a limited number of resources, such as power and spectral.
To obtain high spectral efficiency, we use coded modulation (CM), such as bit-interleaved coded modulation (BICM) and delayed BICM (DBICM). To be specific, BICM is a pragmatic implementation of CM which has been largely adopted in both industry and academia. While BICM approaches CM capacity at high rates, the capacity gap between BICM and CM is still noticeable at lower code rates. To tackle this problem, DBICM, as a variation of BICM, introduces a delay module to create a dependency between multiple codewords, which enables us to exploit extrinsic information from the decoded delayed sub-blocks to improve the detection of the undelayed sub-blocks. Recent work shows that DBICM improves capacity over BICM. In addition, BICM and DBICM schemes protect each bit-channel differently, which is often referred to as the unequal error protection (UEP) property. Therefore, bit mapping designs are important for constructing pragmatic BICM and DBICM. To provide reliable communication, we have jointly designed bit mappings in DBICM and irregular low-density parity-check (LDPC) codes. For practical considerations, spatially coupled LDPC (SC-LDPC) codes have been considered as well. Specifically, we have investigated the joint design of the multi-chain SC-LDPC and the BICM bit mapper. In addition, the design of SC-LDPC codes with improved decoding threshold performance and reduced rate loss has been investigated in this thesis as well.
The main body of this thesis consists of three parts. In the first part, considering Gray-labeled square M-ary quadrature amplitude modulation (QAM) constellations, we investigate the optimal delay scheme with the largest spectrum efficiency of DBICM for a fixed maximum number of delayed time slots and a given signal-to-noise ratio. Furthermore, we jointly optimize degree distributions and channel assignments of LDPC codes using protograph-based extrinsic information transfer charts. In addition, we proposed a constrained progressive edge growth-like algorithm to jointly construct LDPC codes and bit mappings for DBICM, taking the capacity of each bit-channel into account. Simulation results demonstrate that the designed LDPC-coded DBICM systems significantly outperform LDPC-coded BICM systems. In the second part, we proposed a windowed decoding algorithm for DBICM, which uses the extrinsic information of both the decoded delayed and undelayed sub-blocks, to improve the detection for all sub-blocks. We show that the proposed windowed decoding significantly outperforms the original decoding, demonstrating the effectiveness of the proposed decoding algorithm. In the third part, we apply multi-chain SC-LDPC to BICM. We investigate various connections for multi-chain SC-LDPC codes and bit mapping designs and analyze the performance of the multi-chain SC-LDPC codes over the equivalent binary erasure channels via density evolution. Numerical results demonstrate the superiority of the proposed design over existing connected-chain ensembles and over single-chain ensembles with the existing bit mapping design
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
A Reliable Multiple Access Scheme Based on Chirp Spread Spectrum and Turbo Codes
Nowadays, smart devices are the indispensable part of everyone's life and they play
an important role in the advancement of industries and businesses.These devices are able to
communicate with themselves and build the super network of the Internet of Things(IoT).
Therefore, the need for the underlying structure of wireless data communications gains
momentum. We require a wireless communication to support massive connectivity with
ultra-fast data transmission rate and ultra-low latency. This research explores two possible
methods of tackling the issues of the current communication systems for getting closer to
the realization of the IoT. First, a grant-free scheme for uplink communication is proposed.
The idea is to the combine the control signals with data signals by superimposing them on
top of each other with minimal degradation of both signals. Moreover, it is well-established
that orthogonal multiple access schemes cannot support the massive connectivity. Ergo, the second part of this research investigates a Non-Orthogonal Multiple Access(NOMA) scheme
that exploits the powerful notion of turbo codes for separating the signals in a slow fading
channel. It has been shown that in spite of the simplicity of the design, it has the potentials
to surpass the performance of Sparse Code Multiple Access(SCMA) scheme
Asynchronous techniques for system-on-chip design
SoC design will require asynchronous techniques as the large parameter variations across the chip will make it impossible to control delays in clock networks and other global signals efficiently. Initially, SoCs will be globally asynchronous and locally synchronous (GALS). But the complexity of the numerous asynchronous/synchronous interfaces required in a GALS will eventually lead to entirely asynchronous solutions. This paper introduces the main design principles, methods, and building blocks for asynchronous VLSI systems, with an emphasis on communication and synchronization. Asynchronous circuits with the only delay assumption of isochronic forks are called quasi-delay-insensitive (QDI). QDI is used in the paper as the basis for asynchronous logic. The paper discusses asynchronous handshake protocols for communication and the notion of validity/neutrality tests, and completion tree. Basic building blocks for sequencing, storage, function evaluation, and buses are described, and two alternative methods for the implementation of an arbitrary computation are explained. Issues of arbitration, and synchronization play an important role in complex distributed systems and especially in GALS. The two main asynchronous/synchronous interfaces needed in GALS-one based on synchronizer, the other on stoppable clock-are described and analyzed
Improving Bandwidth Utilization in a 1 Tbps Airborne MIMO Communications Downlink
FEC techniques are compared for different MIMO configurations of a high altitude, extremely wide bandwidth radio frequency downlink. Monte Carlo simulations are completed in MATLAB® with the aim of isolating the impacts of turbo codes and LDPC codes on system throughput and error performance. The system is modeled as a transmit-only static array at an altitude of 60,000 feet, with no interferers in the channel. Transmissions are received by a static receiver array. Simulations attempt to determine what modulation types should be considered for practical implementation, and what FEC codes enable these modulation schemes. The antenna configurations used in this study are [44:352], [62:248], and [80:160] transmitters to receivers. Effects from waveform generation, mixing, down-conversion, and amplification are not considered. Criteria of interest were BER and throughput, with the maximum allowable value of the former set at 1 x 10-5, and the latter set at a 1 terabits per second (Tbps) transfer rate for a successful configuration. Results show that the best performing system configuration was unable to meet both criteria, but was capable of improving over Brueggen\u27s 2012 research, which used Reed-Solomon codes and a MIMO configuration of [80:160], by 18.6%. The best-case configuration produced a throughput rate of 0.83 Tbps at a BER of less than 1 x 10-8, by implementing a rate 2/3 LDPC code with QAM constellation of 16 symbols
Machine Learning in Digital Signal Processing for Optical Transmission Systems
The future demand for digital information will exceed the capabilities of current optical communication systems, which are approaching their limits due to component and fiber intrinsic non-linear effects. Machine learning methods are promising to find new ways of leverage the available resources and to explore new solutions. Although, some of the machine learning methods such as adaptive non-linear filtering and probabilistic modeling are not novel in the field of telecommunication, enhanced powerful architecture designs together with increasing computing power make it possible to tackle more complex problems today. The methods presented in this work apply machine learning on optical communication systems with two main contributions. First, an unsupervised learning algorithm with embedded additive white Gaussian noise (AWGN) channel and appropriate power constraint is trained end-to-end, learning a geometric constellation shape for lowest bit-error rates over amplified and unamplified links. Second, supervised machine learning methods, especially deep neural networks with and without internal cyclical connections, are investigated to combat linear and non-linear inter-symbol interference (ISI) as well as colored noise effects introduced by the components and the fiber. On high-bandwidth coherent optical transmission setups their performances and complexities are experimentally evaluated and benchmarked against conventional digital signal processing (DSP) approaches. This thesis shows how machine learning can be applied to optical communication systems. In particular, it is demonstrated that machine learning is a viable designing and DSP tool to increase the capabilities of optical communication systems
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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