Turbo space-time coding for mimo systems : designs and analyses

Multiple input multiple output (MIMO) systems can provide high diversity, high data rate or a mix of both, for wireless communications. This dissertation combines both modes and suggests analyses and techniques that advance the state of the art of MIMO systems. Specifically, this dissertation studies turbo space-time coding schemes for MIMO systems. Before the designs of turbo space-time codes are presented, a fundamental tool to analyze and design turbo coding schemes, the extrinsic information transfer (EXIT) chart method, is extended from the binary/nonbinary code case to coded modulation case. This extension prepares the convergence analysis for turbo space-time code. Turbo space-time codes with symbols precoded by randomly chosen unitary time variant linear transformations (TVLT) are investigated in this dissertation. It is shown that turbo codes with TVLT achieve full diversity gain and good coding gain with high probability. The probability that these design goals are not met is shown to vanish exponentially with the Hamming distance between codewords (number of different columns). Hence, exhaustive tests of the rank and the determinant criterion are not required. As an additional benefit of the application of TVLT, with the removal of the constant modulation condition, it is proved that throughput rates achieved by these codes are significantly higher than the rates achievable by conventional space-time codes. Finally, an EXIT chart analysis for turbo space-time codes with TVLT is developed, with application to predicting frame error rate (FER) performance without running full simulation. To increase the data rate of turbo-STC without exponentially increasing the decoding complexity, a multilevel turbo space-time coding scheme with TVLT is proposed. An iterative joint demapping and decoding receiver algorithm is also proposed. For MIMO systems with a large number of transmit antennas, two types of layered turbo space-time (LTST) coding schemes are studied. For systems with low order modulation, a type of LTST with a vertical encoding structure and a low complexity parallel interference cancellation (PlC) receiver is shown to achieve close to capacity performance. For high order modulation, another type of LTST with a horizontal encoding structure, TVLT, and an ordered successive interference cancellation (OSIC) receiver is shown to achieve better performance than conventional layered space-time coding schemes, where ordering is not available in the SIC detection

The Road From Classical to Quantum Codes: A Hashing Bound Approaching Design Procedure

Powerful Quantum Error Correction Codes (QECCs) are required for stabilizing and protecting fragile qubits against the undesirable effects of quantum decoherence. Similar to classical codes, hashing bound approaching QECCs may be designed by exploiting a concatenated code structure, which invokes iterative decoding. Therefore, in this paper we provide an extensive step-by-step tutorial for designing EXtrinsic Information Transfer (EXIT) chart aided concatenated quantum codes based on the underlying quantum-to-classical isomorphism. These design lessons are then exemplified in the context of our proposed Quantum Irregular Convolutional Code (QIRCC), which constitutes the outer component of a concatenated quantum code. The proposed QIRCC can be dynamically adapted to match any given inner code using EXIT charts, hence achieving a performance close to the hashing bound. It is demonstrated that our QIRCC-based optimized design is capable of operating within 0.4 dB of the noise limit

Low-Complexity Approaches to Slepian–Wolf Near-Lossless Distributed Data Compression

This paper discusses the Slepian–Wolf problem of distributed near-lossless compression of correlated sources. We introduce practical new tools for communicating at all rates in the achievable region. The technique employs a simple “source-splitting” strategy that does not require common sources of randomness at the encoders and decoders. This approach allows for pipelined encoding and decoding so that the system operates with the complexity of a single user encoder and decoder. Moreover, when this splitting approach is used in conjunction with iterative decoding methods, it produces a significant simplification of the decoding process. We demonstrate this approach for synthetically generated data. Finally, we consider the Slepian–Wolf problem when linear codes are used as syndrome-formers and consider a linear programming relaxation to maximum-likelihood (ML) sequence decoding. We note that the fractional vertices of the relaxed polytope compete with the optimal solution in a manner analogous to that observed when the “min-sum” iterative decoding algorithm is applied. This relaxation exhibits the ML-certificate property: if an integral solution is found, it is the ML solution. For symmetric binary joint distributions, we show that selecting easily constructable “expander”-style low-density parity check codes (LDPCs) as syndrome-formers admits a positive error exponent and therefore provably good performance

Hardness of decoding quantum stabilizer codes

In this article we address the computational hardness of optimally decoding a quantum stabilizer code. Much like classical linear codes, errors are detected by measuring certain check operators which yield an error syndrome, and the decoding problem consists of determining the most likely recovery given the syndrome. The corresponding classical problem is known to be NP-complete, and a similar decoding problem for quantum codes is also known to be NP-complete. However, this decoding strategy is not optimal in the quantum setting as it does not take into account error degeneracy, which causes distinct errors to have the same effect on the code. Here, we show that optimal decoding of stabilizer codes is computationally much harder than optimal decoding of classical linear codes, it is #P

Ka-Band Link Study and Analysis for a Mars Hybrid RF/Optical Software Defined Radio

The integrated radio and optical communications (iROC) project at the NASA Glenn Research Center (GRC) is investigating the feasibility of a hybrid RF and optical communication subsystem for future deep space missions. The hybrid communications subsystem enables the advancement of optical communications while simultaneously mitigating the risk of infusion by combining an experimental optical transmitter and telescope with a reliable Ka-band RF transmitter and antenna. The iROC communications subsystem seeks to maximize the total data return over the course of a potential 2-year mission in Mars orbit beginning in 2021. Although optical communication by itself offers potential for greater data return over RF, the reliable Ka-band link is also being designed for high data return capability in this hybrid system. A daily analysis of the RF link budget over the 2-year span is performed to optimize and provide detailed estimates of the RF data return. In particular, the bandwidth dependence of these data return estimates is analyzed for candidate waveforms. In this effort, a data return modeling tool was created to analyze candidate RF modulation and coding schemes with respect to their spectral efficiency, amplifier output power back-off, required digital to analog conversion (DAC) sampling rates, and support by ground receivers. A set of RF waveforms is recommended for use on the iROC platform