Low Complexity Time-Concatenated Turbo Equalization for Block Transmission Without Guard Interval: Part 1—The Concept

This paper proposes a novel time-concatenated turbo equalization technique, chained turbo equalization (CHATUE), that allows block transmission systems to eliminate the guard interval (GI), while achieving excellent performance. The proposed CHATUE algorithm connects turbo equalizers neighboring in time, so that they exchange information about their inter-block-interference components in the form of a posteriori log-likelihood ratio. The latest version of the low complexity sub-optimal turbo equalization technique for block-wise single carrier transmission, frequency domain soft cancellation and minimum mean squared error, is fully exploited in developing the CHATUE algorithm. Results of extrinsic information transfer chart analysis as well as a series of bit-error rate (BER) simulations show that excellent performances can be achieved without imposing heavy computational burden in multipath-rich (quasi-static) block Rayleigh fading channels. It is shown that, if the information bit-rate is kept identical (because it may be unpreferable for the industry to change the frame structure), the CHATUE algorithm achieves lower BER than that with block transmission with GI, because lower rate (strong) code for error protection can be used by utilizing the time-duration made available by eliminating the GI. In addition, by combining the proposed structure with a simple rate-1 doped accumulator, further BER improvement exhibiting clear turbo cliff can be achieved. A sister paper (a Part-2 paper) applies the proposed CHATUE algorithm to single carrier frequency division multiple access systems Hui et al. (Wirel Pers Commun, 2011)

Channel Coding in Molecular Communication

This dissertation establishes and analyzes a complete molecular transmission system from a communication engineering perspective. Its focus is on diffusion-based molecular communication in an unbounded three-dimensional fluid medium. As a basis for the investigation of transmission algorithms, an equivalent discrete-time channel model (EDTCM) is developed and the characterization of the channel is described by an analytical derivation, a random walk based simulation, a trained artificial neural network (ANN), and a proof of concept testbed setup. The investigated transmission algorithms cover modulation schemes at the transmitter side, as well as channel equalizers and detectors at the receiver side. In addition to the evaluation of state-of-the-art techniques and the introduction of orthogonal frequency-division multiplexing (OFDM), the novel variable concentration shift keying (VCSK) modulation adapted to the diffusion-based transmission channel, the lowcomplex adaptive threshold detector (ATD) working without explicit channel knowledge, the low-complex soft-output piecewise linear detector (PLD), and the optimal a posteriori probability (APP) detector are of particular importance and treated. To improve the error-prone information transmission, block codes, convolutional codes, line codes, spreading codes and spatial codes are investigated. The analysis is carried out under various approaches of normalization and gains or losses compared to the uncoded transmission are highlighted. In addition to state-of-the-art forward error correction (FEC) codes, novel line codes adapted to the error statistics of the diffusion-based channel are proposed. Moreover, the turbo principle is introduced into the field of molecular communication, where extrinsic information is exchanged iteratively between detector and decoder. By means of an extrinsic information transfer (EXIT) chart analysis, the potential of the iterative processing is shown and the communication channel capacity is computed, which represents the theoretical performance limit for the system under investigation. In addition, the construction of an irregular convolutional code (IRCC) using the EXIT chart is presented and its performance capability is demonstrated. For the evaluation of all considered transmission algorithms the bit error rate (BER) performance is chosen. The BER is determined by means of Monte Carlo simulations and for some algorithms by theoretical derivation

Sparse graph-based coding schemes for continuous phase modulations

The use of the continuous phase modulation (CPM) is interesting when the channel represents a strong non-linearity and in the case of limited spectral support; particularly for the uplink, where the satellite holds an amplifier per carrier, and for downlinks where the terminal equipment works very close to the saturation region. Numerous studies have been conducted on this issue but the proposed solutions use iterative CPM demodulation/decoding concatenated with convolutional or block error correcting codes. The use of LDPC codes has not yet been introduced. Particularly, no works, to our knowledge, have been done on the optimization of sparse graph-based codes adapted for the context described here. In this study, we propose to perform the asymptotic analysis and the design of turbo-CPM systems based on the optimization of sparse graph-based codes. Moreover, an analysis on the corresponding receiver will be done

Cloud Radio Access Network in Constrained Fronthaul

The Cloud Radio Access Network (C-RAN) has been proposed for the provision of advanced fourth and fifth generation wireless communication services. The C-RAN system have been shown to reduce costs, and can provide high spectral efficiency and energy efficiency. The fronthaul in such networks, defined as the transmission links between Remote Radio Units (RRUs) and a central Baseband Unit (BBU), usually has high fronthaul load and constrained capacity. In this thesis, we explore and investigate the basic C-RAN system structure, based on which we propose two developed C-RAN systems. With each system we evaluate the Bit Error Ratio (BER) performance and transmission efficiency in multiple scenarios, and give advanced solutions to reduce the fronthaul load. We also analyse the effect of quantization on BPSK and QPSK modulation schemes, with different detection methods. Error control in fronthaul transmission is considered as erroneous frames may be received at the BBU. Error Detection Coding and Error Correction Coding approaches can be applied to the fronthaul network. They may increase the fronthaul latency, but great improve the end-to-end BER performance. Source compression techniques such as Slepian-Wolf (SW) coding can compress two correlated sources separately and de-compress them jointly. Since each RRU serves many user terminals, and some of them may also be served by another neighbour RRU, which results similarly in correlation of the received data between two RRUs. In this thesis, we applied the SW code to the C-RAN system and evaluate the compression rate achieved in fronthaul networks

LDPC code-based bandwidth efficient coding schemes for wireless communications

This dissertation deals with the design of bandwidth-efficient coding schemes with Low-Density Parity-Check (LDPC) for reliable wireless communications. Code design for wireless channels roughly falls into three categories: (1) when channel state information (CSI) is known only to the receiver (2) more practical case of partial CSI at the receiver when the channel has to be estimated (3) when CSI is known to the receiver as well as the transmitter. We consider coding schemes for all the above categories. For the first scenario, we describe a bandwidth efficient scheme which uses highorder constellations such as QAM over both AWGN as well as fading channels. We propose a simple design with LDPC codes which combines the good properties of Multi-level Coding (MLC) and bit-interleaved coded-modulation (BICM) schemes. Through simulations, we show that the proposed scheme performs better than MLC for short-medium lengths on AWGN and block-fading channels. For the first case, we also characterize the rate-diversity tradeoff of MIMO-OFDM and SISO-OFDM systems. We design optimal coding schemes which achieve this tradeoff when transmission is from a constrained constellation. Through simulations, we show that with a sub-optimal iterative decoder, the performance of this coding scheme is very close to the optimal limit for MIMO (flat quasi-static fading), MIMO-OFDM and SISO OFDM systems. For the second case, we design non-systematic Irregular Repeat Accumulate (IRA) codes, which are a special class of LDPC codes, for Inter-Symbol Interference (ISI) fading channels when CSI is estimated at the receiver. We use Orthogonal Frequency Division Multiplexing (OFDM) to convert the ISI fading channel into parallel flat fading subchannels. We use a simple receiver structure that performs iterative channel estimation and decoding and use non-systematic IRA codes that are optimized for this receiver. This combination is shown to perform very close to a receiver with perfect CSI and is also shown to be robust to change in the number of channel taps and Doppler. For the third case, we look at bandwidth efficient schemes for fading channels that perform close to capacity when the channel state information is known at the transmitter as well as the receiver. Schemes that achieve capacity with a Gaussian codebook for the above system are already known but not for constrained constellations. We derive the near-optimum scheme to achieve capacity with constrained constellations and then propose coding schemes which perform close to capacity. Through linear transformations, a MIMO system can be converted into non-interfering parallel subchannels and we further extend the proposed coding schemes to the MIMO case too

LDPC code-based bandwidth efficient coding schemes for wireless communications

This dissertation deals with the design of bandwidth-efficient coding schemes with Low-Density Parity-Check (LDPC) for reliable wireless communications. Code design for wireless channels roughly falls into three categories: (1) when channel state information (CSI) is known only to the receiver (2) more practical case of partial CSI at the receiver when the channel has to be estimated (3) when CSI is known to the receiver as well as the transmitter. We consider coding schemes for all the above categories. For the first scenario, we describe a bandwidth efficient scheme which uses highorder constellations such as QAM over both AWGN as well as fading channels. We propose a simple design with LDPC codes which combines the good properties of Multi-level Coding (MLC) and bit-interleaved coded-modulation (BICM) schemes. Through simulations, we show that the proposed scheme performs better than MLC for short-medium lengths on AWGN and block-fading channels. For the first case, we also characterize the rate-diversity tradeoff of MIMO-OFDM and SISO-OFDM systems. We design optimal coding schemes which achieve this tradeoff when transmission is from a constrained constellation. Through simulations, we show that with a sub-optimal iterative decoder, the performance of this coding scheme is very close to the optimal limit for MIMO (flat quasi-static fading), MIMO-OFDM and SISO OFDM systems. For the second case, we design non-systematic Irregular Repeat Accumulate (IRA) codes, which are a special class of LDPC codes, for Inter-Symbol Interference (ISI) fading channels when CSI is estimated at the receiver. We use Orthogonal Frequency Division Multiplexing (OFDM) to convert the ISI fading channel into parallel flat fading subchannels. We use a simple receiver structure that performs iterative channel estimation and decoding and use non-systematic IRA codes that are optimized for this receiver. This combination is shown to perform very close to a receiver with perfect CSI and is also shown to be robust to change in the number of channel taps and Doppler. For the third case, we look at bandwidth efficient schemes for fading channels that perform close to capacity when the channel state information is known at the transmitter as well as the receiver. Schemes that achieve capacity with a Gaussian codebook for the above system are already known but not for constrained constellations. We derive the near-optimum scheme to achieve capacity with constrained constellations and then propose coding schemes which perform close to capacity. Through linear transformations, a MIMO system can be converted into non-interfering parallel subchannels and we further extend the proposed coding schemes to the MIMO case too

10th EASN International Conference on Innovation in Aviation & Space to the Satisfaction of the European Citizens

This Special Issue book contains selected papers from works presented at the 10th EASN (European Aeronautics Science Network) International Conference on Innovation in Aviation & Space, which was held from the 2nd until the 4th of September, 2020. About 350 remote participants contributed to a high-level scientific gathering providing some of the latest research results on the topic, as well as some of the latest relevant technological advancements. Eleven interesting articles, which cover a wide range of topics including characterization, analysis and design, as well as numerical simulation, are contained in this Special Issue

NASA Tech Briefs, December 1990

Topics: New Product Ideas; NASA TU Services; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences; Life Sciences