This work deals with communication over the AWGN channel with additive discrete interference, where the sequence of interference symbols is known causally at the transmitter. We use Shannon's treatment for channels with side information at the transmitter as a framework to derive ``optimal precoding" and ``channel code design criterion" for the channel with known interference at the transmitter. Communication over Shannon's state-dependent discrete memoryless channel where the state sequence is known causally at the transmitter requires encoding over the so-called \emph{associated} channel which has exponential input alphabet cardinality with respect to the number of states. We show that by using at most linearly many input symbols of the \emph{associated} channel, the capacity is achievable. In particular, we consider $M$-ary signal transmission over the AWGN channel with additive $Q$-ary interference where the sequence of i.i.d. interference symbols is known causally at the transmitter. We investigate the problem of maximization of the transmission rate under the uniformity constraint, where the channel input given any current interference symbol is uniformly distributed over the channel input alphabet. For this setting, we propose the general structure of a communication system with optimal precoding. We also investigate the extension of the proposed precoding scheme to continuous channel input alphabet. We also consider the problem of channel code design with causal side information at the encoder. We derive the code design criterion at high SNR by defining a new distance measure between the input symbols of the Shannon's \emph{associated} channel. For the case of the binary-input channel, i.e., $M=2$, we show that it is sufficient to use only two (out of $2^Q$) input symbols of the \emph{associated} channel in encoding as far as the distance spectrum of code is concerned. This reduces the problem of channel code design for the binary-input AWGN channel with known interference at the encoder to design of binary codes for the binary symmetric channel where the Hamming distance among codewords is the major factor in the performance of the code.

This work deals with communication over the AWGN channel with additive discrete interference, where the sequence of interference symbols is known causally at the transmitter. We use Shannon's treatment for channels with side information at the transmitter as a framework to derive ``optimal precoding" and ``channel code design criterion" for the channel with known interference at the transmitter. Communication over Shannon's state-dependent discrete memoryless channel where the state sequence is known causally at the transmitter requires encoding over the so-called \emph{associated} channel which has exponential input alphabet cardinality with respect to the number of states. We show that by using at most linearly many input symbols of the \emph{associated} channel, the capacity is achievable. In particular, we consider $M$-ary signal transmission over the AWGN channel with additive $Q$-ary interference where the sequence of i.i.d. interference symbols is known causally at the transmitter. We investigate the problem of maximization of the transmission rate under the uniformity constraint, where the channel input given any current interference symbol is uniformly distributed over the channel input alphabet. For this setting, we propose the general structure of a communication system with optimal precoding. We also investigate the extension of the proposed precoding scheme to continuous channel input alphabet. We also consider the problem of channel code design with causal side information at the encoder. We derive the code design criterion at high SNR by defining a new distance measure between the input symbols of the Shannon's \emph{associated} channel. For the case of the binary-input channel, i.e., $M=2$, we show that it is sufficient to use only two (out of $2^Q$) input symbols of the \emph{associated} channel in encoding as far as the distance spectrum of code is concerned. This reduces the problem of channel code design for the binary-input AWGN channel with known interference at the encoder to design of binary codes for the binary symmetric channel where the Hamming distance among codewords is the major factor in the performance of the code.

Non-volatile memories (NVM) including flash memories and resistive memories have attracted significant interest as data storage media. Flash memories are widely employed in mobile devices and solid-state drives (SSD). Resistive memories are promising as storage class memory and embedded memory applications. Data reliability is the fundamental requirement of NVM as data storage media. However, modern nano-scale NVM suffers from challenges of inter-cell interference (ICI), charge leakage, and write endurance, which threaten the reliability of stored data. In order to cope with these adverse effects, advanced coding techniques including soft decision decoding have been investigated actively. However, current coding techniques do not capture the physical properties of NVM well, so the improvement of data reliability is limited. Although soft decision decoding improves the data reliability by using soft decision values, it degrades read speed performance due to multiple read operations needed to obtain soft decision values. In this dissertation, we explore coding schemes that use side information corresponding to the physical phenomena to improve the data reliability significantly. The side information is obtained before writing data into memory and incorporated during the encoding stage. Hence, the proposed coding schemes maintain the read speed whereas the write speed performance would be degraded. It is a big advantage from the perspective of speed performance since the read speed is more critical than the write speed in many memory applications. First, this dissertation investigates the coding techniques for memory with stuckat defects. The idea of coding techniques for memory with stuck-at defects is employed to handle critical problems of flash memories and resistive memories. For 2D planar flash memories, we propose a coding scheme that combats the ICI, which is a primary challenge of 2D planar flash memories. Also, we propose a coding scheme that reduces the effect of fast detrapping, a degradation factor in 3D vertical flash memories. Finally, we investigate the coding techniques that improve write endurance and power consumption of resistive memories.

The performance of multiple input single output (MISO) broadcast channels is strongly dependent on the availability of channel side information (CSI) at the transmitter. In many practical systems, CSI may be available to the transmitter only in a corrupted and incomplete form. It is natural to assume that the flaws in the CSI are random and can be represented by a probability distribution over the channel. This work is concerned with two key issues concerning MISO broadcast systems with random CSI: performance analysis and system design. First, the impact of noisy channel information on system performance is investigated. A simple model is formulated where the channel is Rayleigh fading, the CSI is corrupted by additive white Gaussian noise and a zero forcing precoder is formed by the noisy CSI. Detailed analysis of the ergodic rate and outage probability of the system is given. Particular attention is given to system behavior at asymptotically high SNR. Next, a method to construct precoders in a manner that accounts for the uncertainty in the channel information is developed. A framework is introduced that allows one to quantify the tradeoff between the risk (due to the CSI randomness) that is associated with a precoder and the resulting transmission rate. Using ideas from modern portfolio theory, the risk-rate problem is modified to a tractable mean-variance optimization problem. Thus, we give a method that allows one to efficiently find a good precoder in the risk-rate sense. The technique is quite general and applies to a wide range of CSI probability distributions.

The performance of multiple input single output (MISO) broadcast channels is strongly dependent on the availability of channel side information (CSI) at the transmitter. In many practical systems, CSI may be available to the transmitter only in a corrupted and incomplete form. It is natural to assume that the flaws in the CSI are random and can be represented by a probability distribution over the channel. This work is concerned with two key issues concerning MISO broadcast systems with random CSI: performance analysis and system design. First, the impact of noisy channel information on system performance is investigated. A simple model is formulated where the channel is Rayleigh fading, the CSI is corrupted by additive white Gaussian noise and a zero forcing precoder is formed by the noisy CSI. Detailed analysis of the ergodic rate and outage probability of the system is given. Particular attention is given to system behavior at asymptotically high SNR. Next, a method to construct precoders in a manner that accounts for the uncertainty in the channel information is developed. A framework is introduced that allows one to quantify the tradeoff between the risk (due to the CSI randomness) that is associated with a precoder and the resulting transmission rate. Using ideas from modern portfolio theory, the risk-rate problem is modified to a tractable mean-variance optimization problem. Thus, we give a method that allows one to efficiently find a good precoder in the risk-rate sense. The technique is quite general and applies to a wide range of CSI probability distributions.

This report presents a survey of the state-of-the-art methods for building recommendation systems. The report mainly concentrates on systems that use the available side information in addition to a fraction of known affinity values such as ratings. Such data is referred to as Dyadic Data with Covariates (DyadC). The sources of side information being considered includes user/item entity attributes, temporal information and social network attributes. Further, two new models for recommendation systems that make use of the available side information within the collaborative filtering (CF) framework, are proposed. Review Quality Aware Collaborative Filtering, uses external side information, especially review text to evaluate the quality of available ratings. These quality scores are then incorporated into probabilistic matrix factorization (PMF) to develop a weighted PMF model for recommendation. The second model, Mixed Membership Bayesian Affinity Estimation (MMBAE), is based on the paradigm of Simultaneous Decomposition and Prediction (SDaP). This model simultaneously learns mixed membership cluster assignments for users and items along with a predictive model for rating prediction within each co-cluster. Experimental evaluation on benchmark datasets are provided for these two models. / text

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The turbo code is a block code even though a convolutional encoder is used to construct codewords. Its performance depends on the code word length. Since the invention of the turbo code in 1993, most of the bit error rate (BER) evaluations have been performed using large block sizes, i.e., sizes greater than 1000, or even 10,000. However, for telemetry and command, a relatively short message (<500 bits) may be used. This paper investigates the turbo-coded BER performance for short packets. Fading channel is also considered. In addition, biased channel side information is adopted to improve the performance.

This thesis deals with the Shannon-theoretic fundamental limits of channel coding for single-user channels with memory and feedback and for multi-user channels with side information. We first consider the feedback capacity of a class of symmetric channels with memory modelled as nite-state Markov channels. The symmetry yields the existence of a hidden Markov noise process that facilitates the channel description as a function of input and noise, where the function satisfies a desirable invertibility property. We show that feedback does not increase capacity for such class of finite-state channels and that both their non-feedback and feedback capacities are achieved by an independent and uniformly distributed input. As a result, the capacity is given as a difference of output and noise entropy rates, where the output is also a hidden Markov process; hence, capacity can be approximated via well known algorithms. We then consider the memoryless state-dependent multiple-access channel (MAC) where the encoders and the decoder are provided with various degrees of asymmetric noisy channel state information (CSI). For the case where the encoders observe causal, asymmetric noisy CSI and the decoder observes complete CSI, inner and outer bounds to the capacity region, which are tight for the sum-rate capacity, are provided. Next, single-letter characterizations for the channel capacity regions under each of the following settings are established: (a) the CSI at the encoders are non-causal and asymmetric deterministic functions of the CSI at the decoder (b) the encoders observe asymmetric noisy CSI with asymmetric delays and the decoder observes complete CSI; (c) a degraded message set scenario with asymmetric noisy CSI at the encoders and complete and/or noisy CSI at the decoder. Finally, we consider the above state-dependent MAC model and identify what is required to be provided to the receiver in order to get a tight converse for the sum-rate capacity. Inspired by the coding schemes of the lossless CEO problem as well as of a recently proposed achievable region, we provide an inner bound which demonstrates the rate required to transmit this information to the receiver. / Thesis (Ph.D, Mathematics & Statistics) -- Queen's University, 2013-07-12 13:48:59.849

High peak to average power ratio (PAPR) is one of the major drawbacks in orthogonal frequency division multiplexing (OFDM) systems. In recently years, various methods have been proposed to reduce the PAPR performance. The selected mapping (SLM) scheme is perhaps the most popular one because it provides outstanding PAPR reduction performance. In addition, the subcarrier magnitude remains the same in the SLM scheme. However, there are two major shortcomings in the SLM scheme. First of all, it requires a number of inverse fast Fourier transforms (IFFTs) to produce candidate signals, dramatically increasing the computational complexity. In addition, side information has to be transmitted to the receiver to indicate the candidate signal that results in the best PAPR, leading to the decrease in bandwidth utilization. To overcome these two drawbacks, this thesis proposes a novel SLM scheme that does not need side information. The proposed scheme is based on a low complexity SLM scheme [C.-P. Li, S.-H. Wang, and C.-L. Wang, ¡§Novel low-complexity SLM schemes for PAPR reduction in OFDM systems,¡¨ IEEE Trans. Signal Process., vol. 58, no. 5, pp. 2916¡V2921, May 2010] in pilot-aided OFDM system. Simulation experiments are conducted to verify the performance of the proposed scheme. It is shown that the bit error rate (BER) performance of the proposed scheme is very similar to that of the traditional SLM scheme with perfect knowledge of the side information. Therefore, the proposed scheme not only has the advantages of low complexity and high bandwidth utilization, but also has a superior BER performance.

Communication networks are an integral part of the Internet of Things (IoT) era. They enable endless opportunities for connectivity in a wide range of applications, leading to advances in efficiency of day-to-day life. While creating opportunities, they also incur several new challenges. In general, we wish to design a system that performs optimally well in all aspects. However, there usually exist competing objectives which lead to tradeoffs. In this thesis, driven by several applications, new features and objectives are included into the system model, making it closer to reality and needs. The results presented in this thesis aim at providing insight into the fundamental tradeoff of the system performance which can serve as a guideline for the optimal design of real-world communication systems. The thesis is divided into two parts. The first part considers the aspect of signal reconstruction requirement as a new objective in the source and channel coding problems. In this part, we consider the framework where the quality and/or availability of the side information can be influenced by a cost-constrained action sequence. In the source coding problem, we impose a constraint on the reconstruction sequence at the receiver that it should be reproduced at the sender, and characterize the fundamental tradeoff in the form of the rate-distortion-cost region, revealing the optimal relation between compression rate, distortion, and action cost. The channel coding counterpart is then studied where a reconstruction constraint is imposed on the channel input sequence such that it should be reconstructed at the receiver. An extension to the multi-stage channel coding problem is also considered where inner and outer bounds to the capacity region are given. The result on the channel capacity reveals interesting consequence of imposing an additional reconstruction requirement on the system model which has a causal processing structure. In the second part, we consider the aspect of information security and privacy in lossy source coding problems. The sender wishes to compress the source sequence in order to satisfy a distortion criterion at the receiver, while revealing only limited knowledge about the source to an unintended user. We consider three different aspects of information privacy. First, we consider privacy of the source sequence against the eavesdropper in the problem of source coding with action-dependent side information. Next, we study privacy of the source sequence due to the presence of a public helper in distributed lossy source coding problems. The public helper is assumed to be either a user who provides side information over a public link which can be eavesdropped, or a legitimate user in the network who helps to relay information to the receiver, but may not ignore the information that is not intended for it. Lastly, we take on a new perspective of information privacy in the source coding problem. That is, instead of protecting the source sequence, we are interested in the privacy of the reconstruction sequence with respect to a user in the system. For above settings, we provide the complete characterization of the rate-distortion(-cost)-leakage/equivocation region or corresponding inner and outer bounds for discrete memoryless systems. / <p>QC 20140514</p>