A blind algorithm is proposed in order to compensate for the phase noise resulting from imperfect oscillators in orthogonal frequency-division multiplexing (OFDM) systems over constant modulus modulation. In the proposed algorithm, one received OFDM symbol is partitioned into subblocks in the time domain and the phase noise over each subblock is approximated as its time-average. Under the approximation, the squared magnitude of the channel gain multiplied by the data symbol at each subcarrier is shown to be expressed in terms of these time-averages and the discrete Fourier transform (DFT) coefficients of the received samples at each subblock with zero padding. Based on the relation, the proposed algorithm compensates for the phase noise without pilot symbols. Numerical results show that the proposed algorithm outperforms conventional algorithms as well as it requires lower computational complexity.

To achieve a low error rate of NAND flash memory, reliable reference voltages should be updated based on the accurate knowledge of program/erase (P/E) cycles and retention time, because those severely distort the threshold voltage distribution of memory cell. Due to the sensitivity to the temperature, however, a flash memory controller is unable to acquire the exact knowledge of retention time, meaning that it is challenging to estimate accurate read reference voltages in practice. In this paper, we propose a novel machine-learning-based read reference voltage estimation framework for the NAND flash memory systems without the knowledge of retention time. To establish an unknown input-output relation of the estimation model, we derive input features by sensing and decoding memory cells in the minimum read unit. In order to define the relation between unlabeled input features and a pre-assigned class label, namely label read reference voltages, we propose three mapping functions: 1) k-nearest neighborsbased, 2) nearest-centroid-based, and 3) polynomial regression-based read reference voltage estimators. For the proposed estimation schemes, we analyze that the storage overhead and computational complexity are increasing function of the exploited feature dimension. Accordingly, we propose a feature selection (or dimension reduction) algorithm to select the minimum dimension and corresponding features to reduce the overhead and complexity while maintaining high estimation accuracy. Based on extensive numerical analysis, we validate that the derived features successfully replace unknown knowledge of retention time, and the proposed feature selection algorithm precisely adjusts the trade-off between overhead/complexity and estimation accuracy. Furthermore, the simulation and analysis results show that the proposed framework not only outperforms the conventional estimation schemes but also achieves the near-optimal frame error rate while sustaining low latency performance.

Since a novel diversity technique called a space–time line code (STLC) was invented, previous studies have focused on the analysis of a rate-1 STLC assuming two receive antennas. For the state-of-the-art STLCs with transmit antenna selection (TAS), in this study, the ergodic capacities of TAS-STLC systems with various code rates are mathematically derived, not only for a TAS-STLC system with two receive antennas but also for those with three or four . To this end, the probability density function of the instantaneous signal-to-noise ratio was characterized. The accuracy of the mathematical analysis was validated by a numerical simulation. This study is significant for investigating the fundamental performance of TAS-STLC systems.

For multiple-input multiple-output systems with four receive antennas, conventional space–time line codes (STLCs) have supported code rates of 3/4, 4/7, and 1/2. To provide a wider range of transmission rates, we herein propose a rate-1 STLC for four-receive-antenna systems. We present an encoding method to achieve full rate and devise a simple decoding scheme that does not require full channel state information at the receiver. Assuming a large number of transmit antennas, we analyze the bit error rate performance and demonstrate that the proposed STLC can achieve full spatial diversity.

High peak-to-average power ratio (PAPR) has been major drawback of orthogonal frequency-division multiplexing (OFDM). To reduce the PAPR in the polar-coded OFDM systems, we propose a polar coding-based selective mapping (SLM) which does not transmit redundant information. Based on a set of independent frozen data blocks, we construct coset codes of a linear polar code to efficiently generate multiple OFDM signals, and selectively transmit the one with the lowest PAPR. Since the proposed SLM does not transmit either the side information or PAPR control labels, we can avoid the data rate loss. We also present an adaptive trial-based blind receiver to perform not only decoding of the unfrozen data block but also detection of the selected signal (or frozen data block). Simulation results show that the PAPR performance of the proposed SLM can approach to the optimal, and the blind receiver can support the proposed SLM with high accuracy.

For an uplink sparse code multiple access (SCMA) system, a codebook-domain superposition transmission can be applied to increase the multiplexing gain by efficient utilization of the codebooks as multiple access resources. However, the destructive collision of superposed codewords can restrict the performance improvement of the system because of the increasing interlayer interferences. In this paper, we analyze the effects of the interlayer interferences on the bit error rates, and optimize the SCMA codebooks that can mitigate the interlayer interferences. Simulation results show that the optimized codebooks can provide a noticeable gain to improve the performance of uplink SCMA systems applied with superposition transmission.