We survey the current state of phase change memory (PCM), a non-volatile solid-state memory technology built around the large electrical contrast between the highly-resistive amorphous and highly-conductive crystalline states in so-called phase change materials. PCM technology has made rapid progress in a short time, having passed older technologies in terms of both sophisticated demonstrations of scaling to small device dimensions, as well as integrated large-array demonstrators with impressive retention, endurance, performance and yield characteristics. We introduce the physics behind PCM technology, assess how its characteristics match up with various potential applications across the memory-storage hierarchy, and discuss its strengths including scalability and rapid switching speed. We then address challenges for the technology, including the design of PCM cells for low RESET current, the need to control device-to-device variability, and undesirable changes in the phase change material that can be induced by the fabrication procedure. We then turn to issues related to operation of PCM devices, including retention, device-to-device thermal crosstalk, endurance, and bias-polarity effects. Several factors that can be expected to enhance PCM in the future are addressed, including Multi-Level Cell technology for PCM (which offers higher density through the use of intermediate resistance states), the role of coding, and possible routes to an ultra-high density PCM technology.Comment: Review articl

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Abstract-In this paper, we consider multiple access schemes with correlated sources. Distributed source coding is not used; rather, the correlation is exploited at the access point (AP). In particular, we assume that each source uses a channel code to transmit, through an additive white Gaussian noise (AWGN) channel, its information to the AP, where component decoders, associated with the sources, iteratively exchange soft information by taking into account the correlation. The key goal of this paper is to investigate whether there exist optimized channel codes for this scenario, i.e., channel codes which guarantee a desired performance level (in terms of average bit error rate, BER) at the lowest possible signal-to-noise ratio (SNR). A twodimensional extrinsic information transfer (EXIT) chart-inspired optimization approach is proposed. Our results suggest that by properly designing serially concatenated convolutional codes (SCCCs), the theoretical performance limits can be approached better than by using parallel concatenated convolutional codes (PCCCs) or low-density parity-check (LDPC) codes. It is also shown that irregular LDPC codes tend to perform better than regular LDPC codes, so that the design of appropriate LDPC codes remains an open issue.

In this paper, we consider serially concatenated schemes with outer novel and efficient Low Density Parity Check (LDPC) codes and inner modulations effective against channel impairments, or LDPC coded modulations. With a pragmatic approach, we show how to design LDPC codes tailored for simple and robust modulation formats, like Differentially Encoded (DE) modulations. The LDPC codes are optimized through the use of a recently proposed analysis technique based on EXtrinsic Information Transfer (EXIT) charts. In particular, we optimize the degree distributions of the LDPC codes, obtaining significant insights into the impact of such distributions on the performance of the proposed concatenated schemes. The EXIT chartbased optimization is confirmed by numerical simulations, considering Differential M-ary Phase Shift Keying (DMPSK) at the transmitter side, and iterative demodulation/decoding at the receiver side. The obtained optimized codes show poor performance if not concatenated with the inner DE. The analysis of the optimized codes shows that the decoding complexity of these codes is lower, with respect to that of standard LDPC codes, i.e., optimized for the additive white Gaussian noise (AWGN) channel.

In this paper, we analyze the performance of Low Density Parity Check (LDPC) codes on memoryless channels. We use a recently proposed analysis technique for iterative decoding based on EXtrinsic Information Transfer (EXIT) charts. We show that, based on this technique, the predicted performance of an LDPC code does not depend on the specific memoryless channel, but only on the mutual information (MI) between the input and the output of the channel. As a validation of this conjecture, we evaluate the performance of some LDPC codes over five representative memoryless channels and we compare them, obtaining results in excellent agreement with our conjecture.

Abstract-In this paper, we consider multiple access schemes with correlated sources, where a priori information, in terms of source correlation, is available at the access point (AP). In particular, we assume that each source uses a proper low-density parity-check (LDPC) code to transmit, through an additive white Gaussian noise (AWGN) channel, its information sequence to the AP. At the AP, the information sequences are recovered by an iterative decoder, with component decoders associated with the sources, which exploit the available a priori information. In order to analyze the behaviour of the considered multiple access coded system, we propose a density evolution-based approach, which allows to determine a signal-to-noise ratio (SNR) transfer chart and compute the system multi-dimensional SNR feasible region. The proposed technique, besides characterizing the performance of LDPC-coded multiple access scheme, is expedient to design optimized LDPC codes for this application.