Serial turbo trellis coded modulation using a serially concatenated coder

Serial concatenated trellis coded modulation (SCTCM) includes an outer coder, an interleaver, a recursive inner coder and a mapping element. The outer coder receives data to be coded and produces outer coded data. The interleaver permutes the outer coded data to produce interleaved data. The recursive inner coder codes the interleaved data to produce inner coded data. The mapping element maps the inner coded data to a symbol. The recursive inner coder has a structure which facilitates iterative decoding of the symbols at a decoder system. The recursive inner coder and the mapping element are selected to maximize the effective free Euclidean distance of a trellis coded modulator formed from the recursive inner coder and the mapping element. The decoder system includes a demodulation unit, an inner SISO (soft-input soft-output) decoder, a deinterleaver, an outer SISO decoder, and an interleaver

Energy-efficient design and implementation of turbo codes for wireless sensor network

The objective of this thesis is to apply near Shannon limit Error-Correcting Codes (ECCs), particularly the turbo-like codes, to energy-constrained wireless devices, for the purpose of extending their lifetime. Conventionally, sophisticated ECCs are applied to applications, such as mobile telephone networks or satellite television networks, to facilitate long range and high throughput wireless communication. For low power applications, such as Wireless Sensor Networks (WSNs), these ECCs were considered due to their high decoder complexities. In particular, the energy efficiency of the sensor nodes in WSNs is one of the most important factors in their design. The processing energy consumption required by high complexity ECCs decoders is a significant drawback, which impacts upon the overall energy consumption of the system. However, as Integrated Circuit (IC) processing technology is scaled down, the processing energy consumed by hardware resources reduces exponentially. As a result, near Shannon limit ECCs have recently begun to be considered for use in WSNs to reduce the transmission energy consumption [1,2]. However, to ensure that the transmission energy consumption reduction granted by the employed ECC makes a positive improvement on the overall energy efficiency of the system, the processing energy consumption must still be carefully considered.The main subject of this thesis is to optimise the design of turbo codes at both an algorithmic and a hardware implementation level for WSN scenarios. The communication requirements of the target WSN applications, such as communication distance, channel throughput, network scale, transmission frequency, network topology, etc, are investigated. Those requirements are important factors for designing a channel coding system. Especially when energy resources are limited, the trade-off between the requirements placed on different parameters must be carefully considered, in order to minimise the overall energy consumption. Moreover, based on this investigation, the advantages of employing near Shannon limit ECCs in WSNs are discussed. Low complexity and energy-efficient hardware implementations of the ECC decoders are essential for the target applications

Application of Visual Simulation in Communication Systems

A communications system is a collection of individual communications networks, transmission systems, relay stations, tributary stations, and data terminal equipment (DTE) usually capable of interconnection and interoperation to form an integrated whole. The components of a communications system serve a common purpose, are technically compatible, use common procedures, respond to controls, and operate in unison. A typical communication link includes, at a minimum, three key elements: a transmitter, a communication medium (or channel), and a receiver. The ability to simulate all three of these elements is required in order to successfully model any end-to-end communication system. In order to achieve this target we have used a simulation software “VisSim” ,or Visual Simulator ,that allows us to use a graphical approach to simulation and modeling. With graphical programming, the diagram is the source code, depicted as an arrangement of nodes connected by wires. Each piece of data flows through the wires, to be consumed by nodes that transform the data mathematically or perform some action such as I/O. The visual simulator allows us to model end-to-end communication systems at the signal or physical level. We use VisSim/ Comm to build both transmitter and receiver models, filters and equalizers, as well as channel models and coding techniques from a first principles perspective, by selecting and connecting predefined blocks. In this project work we simulate a variety of models including analog, digital and mixed mode designs, and quickly simulate their behavior using the VisSim/Comm software and graphical programming

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

Channel Estimation in Coded Modulation Systems

With the outstanding performance of coded modulation techniques in fading channels, much research efforts have been carried out on the design of communication systems able to operate at low signal-to-noise ratios (SNRs). From this perspective, the so-called iterative decoding principle has been applied to many signal processing tasks at the receiver: demodulation, detection, decoding, synchronization and channel estimation. Nevertheless, at low SNRs, conventional channel estimators do not perform satisfactorily. This thesis is mainly concerned with channel estimation issues in coded modulation systems where different diversity techniques are exploited to combat fading in single or multiple antenna systems. First, for single antenna systems in fast time-varying fading channels, the thesis focuses on designing a training sequence by exploiting signal space diversity (SSD). Motivated by the power/bandwidth efficiency of the SSD technique, the proposed training sequence inserts pilot bits into the coded bits prior to constellation mapping and signal rotation. This scheme spreads the training sequence during a transmitted codeword and helps the estimator to track fast variation of the channel gains. A comprehensive comparison between the proposed training scheme and the conventional training scheme is then carried out, which reveals several interesting conclusions with respect to both error performance of the system and mean square error of the channel estimator. For multiple antenna systems, different schemes are examined in this thesis for the estimation of block-fading channels. For typical coded modulation systems with multiple antennas, the first scheme makes a distinction between the iteration in the channel estimation and the iteration in the decoding. Then, the estimator begins iteration when the soft output of the decoder at the decoding iteration meets some specified reliability conditions. This scheme guarantees the convergence of the iterative receiver with iterative channel estimator. To accelerate the convergence process and decrease the complexity of successive iterations, in the second scheme, the channel estimator estimates channel state information (CSI) at each iteration with a combination of the training sequence and soft information. For coded modulation systems with precoding technique, in which a precoder is used after the modulator, the training sequence and data symbols are combined using a linear precoder to decrease the required training overhead. The power allocation and the placement of the training sequence to be precoded are obtained based on a lower bound on the mean square error of the channel estimation. It is demonstrated that considerable performance improvement is possible when the training symbols are embedded within data symbols with an equi-spaced pattern. In the last scheme, a joint precoder and training sequence is developed to maximize the achievable coding gain and diversity order under imperfect CSI. In particular, both the asymptotic performance behavior of the system with the precoded training scheme under imperfect CSI and the mean square error of the channel estimation are derived to obtain achievable diversity order and coding gain. Simulation results demonstrate that the joint optimized scheme outperforms the existing training schemes for systems with given precoders in terms of error rate and the amount of training overhead

Estimation and detection techniques for doubly-selective channels in wireless communications

A fundamental problem in communications is the estimation of the channel. The signal transmitted through a communications channel undergoes distortions so that it is often received in an unrecognizable form at the receiver. The receiver must expend significant signal processing effort in order to be able to decode the transmit signal from this received signal. This signal processing requires knowledge of how the channel distorts the transmit signal, i.e. channel knowledge. To maintain a reliable link, the channel must be estimated and tracked by the receiver. The estimation of the channel at the receiver often proceeds by transmission of a signal called the 'pilot' which is known a priori to the receiver. The receiver forms its estimate of the transmitted signal based on how this known signal is distorted by the channel, i.e. it estimates the channel from the received signal and the pilot. This design of the pilot is a function of the modulation, the type of training and the channel. [Continues.