Synchronization for capacity -approaching coded communication systems

The dissertation concentrates on synchronization of capacity approaching error-correction codes that are deployed in noisy channels with very low signal-to-noise ratio (SNR). The major topics are symbol timing synchronization and frame synchronization.;Capacity-approaching error-correction codes, like turbo codes and low-density parity-check (LDPC) codes, are capable of reaching very low bit error rates and frame error rates in noisy channels by iterative decoding. To fully achieve the potential decoding capability of Turbo codes and LDPC codes, proper symbol timing synchronization, frame synchronization and channel state estimation are required. The dissertation proposes a joint estimator of symbol time delay and channel SNR for symbol timing recovery, and a maximum a posteriori (MAP) frame synchronizer for frame synchronization.;Symbol timing recovery is implemented by sampling and interpolation. The received signal is sampled multiple times per symbol period with unknown delay and unknown SNR. A joint estimator estimates the time delay and the SNR. The signal is rebuilt by interpolating available samples using estimated time delay. The intermediate decoding results enable decision-feedback estimation. The estimates of time delay and SNR are refined by iterative processing. This refinement improves the system performance significantly.;Usually the sampling rate is assumed to be a strict integer multiple of the symbol rate. However, in a practical system the local oscillators in the transmitter and the receiver may have random drifts. Therefore the sampling rate is no longer an exact multiple of the symbol rate, and the sampling time follows a random walk. This random walk may harm the system performance severely. The dissertation analyzes the effect of random time walks and proposes to mitigate the effect by overlapped sliding windows and iterative processing.;Frame synchronization is required to find the correct boundaries of codewords. MAP frame synchronization in the sense of minimizing the frame sync failure rate is investigated. The MAP frame synchronizer explores low-density parity-check attributes of the capacity-approaching codes. The accuracy of frame synchronization is adequate for considered coded systems to work reliably under very low SNR

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

Overcoming CubeSat downlink limits with VITAMIN: a new variable coded modulation protocol

Thesis (M.S.) University of Alaska Fairbanks, 2013Many space missions, including low earth orbit CubeSats, communicate in a highly dynamic environment because of variations in geometry, weather, and interference. At the same time, most missions communicate using fixed channel codes, modulations, and symbol rates, resulting in a constant data rate that does not adapt to the dynamic conditions. When conditions are good, the fixed date rate can be far below the theoretical maximum, called the Shannon limit; when conditions are bad, the fixed data rate may not work at all. To move beyond these fixed communications and achieve higher total data volume from emerging high-tech instruments, this thesis investigates the use of error correcting codes and different modulations. Variable coded modulation (VCM) takes advantage of the dynamic link by transmitting more information when the signal-to-noise ratio (SNR) is high. Likewise, VCM can throttle down the information rate when SNR is low without having to stop all communications. VCM outperforms fixed communications which can only operate at a fixed information rate as long as a certain signal threshold is met. This thesis presents a new VCM protocol and tests its performance in both software and hardware simulations. The protocol is geared towards CubeSat downlinks as complexity is focused in the receiver, while the transmission operations are kept simple. This thesis explores bin-packing as a way to optimize the selection of VCM modes based on expected SNR levels over time. Working end-to-end simulations were created using MATLAB and LabVIEW, while the hardware simulations were done with software defined radios. Results show that a CubeSat using VCM communications will deliver twice the data throughput of a fixed communications system

Decoding of Decode and Forward (DF) Relay Protocol using Min-Sum Based Low Density Parity Check (LDPC) System

Decoding high complexity is a major issue to design a decode and forward (DF) relay protocol. Thus, the establishment of low complexity decoding system would beneficial to assist decode and forward relay protocol. This paper reviews existing methods for the min-sum based LDPC decoding system as the low complexity decoding system. Reference lists of chosen articles were further reviewed for associated publications. This paper introduces comprehensive system model representing and describing the methods developed for LDPC based for DF relay protocol. It is consists of a number of components: (1) encoder and modulation at the source node, (2) demodulation, decoding, encoding and modulation at relay node, and (3) demodulation and decoding at the destination node. This paper also proposes a new taxonomy for min-sum based LDPC decoding techniques, highlights some of the most important components such as data used, result performances and profiles the Variable and Check Node (VCN) operation methods that have the potential to be used in DF relay protocol. Min-sum based LDPC decoding methods have the potential to provide an objective measure the best tradeoff between low complexities decoding process and the decoding error performance, and emerge as a cost-effective solution for practical application

Optical Time-Frequency Packing: Principles, Design, Implementation, and Experimental Demonstration

Time-frequency packing (TFP) transmission provides the highest achievable spectral efficiency with a constrained symbol alphabet and detector complexity. In this work, the application of the TFP technique to fiber-optic systems is investigated and experimentally demonstrated. The main theoretical aspects, design guidelines, and implementation issues are discussed, focusing on those aspects which are peculiar to TFP systems. In particular, adaptive compensation of propagation impairments, matched filtering, and maximum a posteriori probability detection are obtained by a combination of a butterfly equalizer and four 8-state parallel Bahl-Cocke-Jelinek-Raviv (BCJR) detectors. A novel algorithm that ensures adaptive equalization, channel estimation, and a proper distribution of tasks between the equalizer and BCJR detectors is proposed. A set of irregular low-density parity-check codes with different rates is designed to operate at low error rates and approach the spectral efficiency limit achievable by TFP at different signal-to-noise ratios. An experimental demonstration of the designed system is finally provided with five dual-polarization QPSK-modulated optical carriers, densely packed in a 100 GHz bandwidth, employing a recirculating loop to test the performance of the system at different transmission distances.Comment: This paper has been accepted for publication in the IEEE/OSA Journal of Lightwave Technolog

Modelaçcão comportamental da camada física NB-IoT - Uplink

Mestrado em Engenharia Eletrónica e TelecomunicaçõesA Internet das Coisas (IoT) consiste numa rede sem fios de sensores/atuadores ligados entre si e que têm a capacidade de recolher dados. Devido ao crescimento rápido do mercado IoT, as redes de longa distância e baixa potência (LPWAN) tornaram-se populares. O NarrowBand-IoT (NB-IoT), desenvolvido pela 3rd Generation Partnership Project (3GPP), é um desses protocolos. O principal objectivo desta dissertação é a implementação de uma simulação comportamental em MATLAB do NB-IoT no uplink, que será disponibilizada abertamente. Esta será focada, primariamente, na camada física e nas suas respetivas funcionalidades, nomeadamente turbo coding, modulação SC-FDMA, modelos de simulação de canal, desmodulação SC-FDMA, estimação de canal, equalizador e turbo decoding. A estimação de canal é feita usando símbolos piloto previamente conhecidos. Os modelos de canal utilizados são baseados nas especificações oficiais da 3GPP. A taxa de bits errados (BER) é calculada e usada de forma a avaliar a performance do turbo encoder e do equalizador zero forcing (ZF). Serve também como comparação quando a implementação usa esquemas de modulação diferentes (Binary Phase-Shift Keying (BPSK) e Quadrature Phase-Shift Keying (QPSK)). Além disso, os sinais gerados em MATLAB são transmitidos usando como front-end de radio-frequência (RF) uma Universal Software Radio Peripheral (USRP). Posteriormente, são recebidos, desmodulados e descodificados. Finalmente, é obtida a constelação do sinal, a BER é calculada e os resultados são analisados.The Internet of Things (IoT) refers to a wireless network of interconnected sensors/actuators with data-collecting technologies. Low Power Wide Area Networks (LPWAN) have become popular due to the rapid growth of the IoT market. Narrowband-IoT (NB-IoT), developed by 3rd Generation Partnership Project (3GPP), is one of these protocols. The main objective of this thesis is the implementation of an open-source uplink behavioral simulator based on MATLAB. Its focus is primarily on Layer 1 (physical layer) relevant functionalities, namely turbo coding, Single-Carrier Frequency-Division Multiple Access (SC-FDMA) modulation, channel modeling, SC-FDMA demodulation, channel estimation, equalization and turbo decoding. Channel estimation is performed using known pilot symbols. The used channel models are based on the 3GPP o cial release specs. The Bit Error Rate (BER) is calculated in order to evaluate the turbo encoder and the Zero Forcing (ZF) equalizer performance, and to compare Binary Phase-Shift Keying (BPSK) and Quadrature Phase-Shift Keying (QPSK) implementations. Furthermore, the MATLAB generated signal is transmitted using a radio-frequency (RF) front-end consisting of an Universal Software Radio Peripheral (USRP). Afterwards, the signal is received, demodulated and decoded. A constellation is obtained, the BER is calculated and the results are analyzed

An Architecture for High Data Rate Very Low Frequency Communication

Very low frequency (VLF) communication is used for long range shore-to-ship broadcasting applications. This paper proposes an architecture for high data rate VLF communication using Gaussian minimum shift keying (GMSK) modulation and low delay parity check (LDPC) channel coding. Non-data aided techniques are designed and used for carrier phase synchronization, symbol timing recovery, and LDPC code frame synchronization. These require the estimation of the operative Eb/N0 for which a kurtosis based algorithm is used. Also, a method for modeling the probability density function of the received signal under the bit condition is presented in this regard. The modeling of atmospheric radio noise (ARN) that corrupts VLF signals is described and an algorithm for signal enhancement in the presence of ARN in given. The BER performance of the communication system is evaluated for bit rates of 400 bps, 600 bps, and 800 bps for communication bandwidth of ~200 Hz.Defence Science Journal, 2013, 63(1), pp.25-33, DOI:http://dx.doi.org/10.14429/dsj.63.376

Low-complexity soft-decision feedback turbo equalization for multilevel modulations

This dissertation proposes two new decision feedback equalization schemes suitable for multilevel modulation systems employing turbo equalization. One is soft-decision feedback equalization (SDFE) that takes into account the reliability of both soft a priori information and soft decisions of the data symbols. The proposed SDFE exhibits lower signal to noise ratio (SNR) threshold that is required for water fall bit error rate (BER) and much faster convergence than the near-optimal exact minimum mean square error linear equalizer (Exact-MMSE-LE) for high-order constellation modulations. The proposed SDFE also offers a low computational complexity compared to the Exact-MMSE-LE. The drawback of the SDFE is that its coefficients cannot reach the matched filter bound (MFB) and therefore after a large number of iterations (e.g. 10), its performance becomes inferior to that of the Exact-MMSE-LE. Therefore, soft feedback intersymbol interference (ISI) canceller-based (SIC) structure is investigated. The SIC structure not only exhibits the same low complexity, low SNR threshold and fast convergence as the SDFE but also reaches the MFB after a large number of iterations. Both theoretical analysis and numerical simulations demonstrate why the SIC achieves MFB while the SDFE cannot. These two turbo equalization structures are also extended from single-input single-output (SISO) systems to multiple-input multiple-output (MIMO) systems and applied in high data-rate underwater acoustic (UWA) communications --Abstract, page iv