High rate space time code with linear decoding complexity for multiple transmitting antennas

The multipath nature of the wireless channel, results in a superposition of the signals of each path at the receiver. This can lead to either constructive or destructive interference. Strong destructive interference is frequently referred to as deep fade and may result in temporary failure of communication due to the severe drop in the channel\u27s signal-to-noise ratio (SNR). To avoid this situation, signal diversity might be introduced. When having more than one antenna at the transmitter and / or receiver, forming a Multiple-Input Multiple-Output (MIMO) channel, spatial diversity can be employed to overcome the fading problem. Space time block codes (STBC) have been shown to be used well with the MIMO channel. Each type of STBC is designed to optimize a different criteria such as rate and diversity, while other characteristics of the code are its error performance and decoding computational complexity. The Orthogonal STBC (OSTBC) family of codes is known to achieve full diversity as well as very simple implementation of the Maximum Likelihood (ML) decoder. However, it was proven that, with complex symbol constellation one cannot achieve a full rate code when the number of transmitting antennas is larger than two. Quasi OSTBC are codes with full rate but with the penalty of more complex decoding, and in general does not achieve full diversity. In this work, new techniques for OSTBC transmission / decoding are explored, such that a full rate code can be transmitted and decoded with linear complexity. The Row Elimination Method (REM) for OSTBC transmission is introduced, which basically involves the transmission of only part of the original OSTBC codeword, resulting in a full rate code termed Semi-Orthogonal STBC (SSTBC). Novel decoding scheme is presented, such that the SSTBC decoding computational complexity remains linear although the transmitted codeword is not orthogonal anymore. A new OSTBC, that complies with the new scheme\u27s requirements, is presented for any number of transmit antennas. The performance of the new scheme is studied under various settings, such as system with limited feedback and multiple antennas at the receiver. The general decoding techniques presented for STBC, assume perfect channel knowledge at the receiver. It was shown, that the performance of any STBC system is severely degraded due to partial channel state information, results from imperfect channel estimation. To minimize the performance loss, one may lengthen the training sequences used for the channel estimation which, inevitably, results in some rate loss. In addition, complex decoding schemes can be used at the receiver to jointly decode the data while enhancing the channel estimation. It is suggested in this work to apply adaptive techniques to mitigate the performance loss without the penalty of additional rate loss or complex decoding. Namely, the bootstrap algorithm is used to further refine the received signals, resulting in better effective rate and performance in the presence of channel estimation errors. Modified implementations for the bootstrap\u27s weights calculation method are also presented, to improve the convergence rate of the algorithm, as well as to maintain a very low computational burden

Study of sequential decoding

Decoding algorithms for data reduction and transmission through noisy space channels using sequential and hybrid computer

Low-Complexity Joint Channel Estimation and List Decoding of Short Codes

A pilot-assisted transmission (PAT) scheme is proposed for short blocklengths, where the pilots are used only to derive an initial channel estimate for the list construction step. The final decision of the message is obtained by applying a non-coherent decoding metric to the codewords composing the list. This allows one to use very few pilots, thus reducing the channel estimation overhead. The method is applied to an ordered statistics decoder for communication over a Rayleigh block-fading channel. Gains of up to $1.2$ dB as compared to traditional PAT schemes are demonstrated for short codes with QPSK signaling. The approach can be generalized to other list decoders, e.g., to list decoding of polar codes.Comment: Accepted at the 12th International ITG Conference on Systems, Communications and Coding (SCC 2019), Rostock, German

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

Coordinated design of coding and modulation systems

The joint optimization of the coding and modulation systems employed in telemetry systems was investigated. Emphasis was placed on formulating inner and outer coding standards used by the Goddard Spaceflight Center. Convolutional codes were found that are nearly optimum for use with Viterbi decoding in the inner coding of concatenated coding systems. A convolutional code, the unit-memory code, was discovered and is ideal for inner system usage because of its byte-oriented structure. Simulations of sequential decoding on the deep-space channel were carried out to compare directly various convolutional codes that are proposed for use in deep-space systems