Channel coding lies at the heart of digital communication and data storage, and this detailed introduction describes the core theory as well as decoding algorithms, implementation details, and performance analyses. In this book, Professors Ryan and Lin provide clear information on modern channel codes, including turbo and low-density parity-check (LDPC) codes. They also present detailed coverage of BCH codes, Reed-Solomon codes, convolutional codes, finite geometry codes, and product codes, providing a one-stop resource for both classical and modern coding techniques. Assuming no prior knowledge in the field of channel coding, the opening chapters begin with basic theory to introduce newcomers to the subject. Later chapters then extend to advanced topics such as code ensemble performance analyses and algebraic code design. 250 varied and stimulating end-of-chapter problems are also included to test and enhance learning, making this an essential resource for students and practitioners alike.

In this work the study has been done on the performance pertaining to the binary antipodal AWGN channel for rate ½ coding approaches, with short and medium blocklengths. This work emphasizes on the contributions of various events leading to block error and their dependence on signal-to-noise ratio, decoder list size, CRC length, if any, and the role of list sorting. Furthermore, this work generalizes to variations, including Reed-Muller/Polar codes that follow the polarization and the method of successive decoding.

We describe a simple modification of the Schmidl-Cox detector for establishing timing in OFDM transmissions that stabilizes performance in transitions from no-signal to signal, or vice-versa. Moreover, the proposed modification scales the detector's metric between 0 and 1 for all scenarios, simplifying threshold setting, and improves timing detector SNR.

We analyze error versus observation time for numerical computing under the stochastic computing paradigm, where operands are encoded with asynchronous sigma-delta modulators. Such encoding offers dramatic savings in energy consumption and/or latency, relative to traditional stochastic computing, at equal RMS error. The paper presents a Fourier analysis of the error with sigma-delta computing for the product of two numerical operands, and presents Matlab error/latency tradeoffs for example operands.

We consider the application of LDPC codes for improving performance in multi-channel (spectrum aggregation) for air-to-ground telemetry, by virtue of frequency diversity available on a wideband frequency-selective multipath channel. Our particular interest is in use of multi-channel OFDM transmission on ‘white spots’ in the microwave spectrum. Each such channel is subject to frequency-selective fading over its bandwidth (typically a few MHz) due to multipath, for which typical OFDM equalization is standard. However, some subcarriers within this OFDM channel may experience deep fading at the output of the equalizer, rendering the symbol error probability poor relative to that on an AWGN channel at the same average SNR. We study simulated performance on a multipath channel described by the ETU fading model. Specific performance reported includes error rate of LDPC coding constrained to a single channel (effective diversity order roughly 2) and error rate of coding across eight channels (diversity order roughly 5). Further, performance on this dispersive fading channel is only about 3 dB worse than that on a no-multipath channel, at block error probability .01.

Asynchronous stochastic computing (ASC) using continuous-time-asynchronous ΣΔ modulators (SC-AΣΔM) has the potential to enable ultra-low-power, on-node machine learning algorithms for the next generation of sensors for the Internet of Things (IoT). Similar to synchronous stochastic computing (SSC 1 ), in SC-AΣΔM complex processing units can be implemented with simple gates because numbers are represented with streams. For example a multiplier is implemented with a XNOR gate, yielding savings in power and area of 90% compared with the typical binary approach. Previous work demonstrated that SC-AΣΔM leverages SSC advantages and addresses its drawbacks, achieving significant savings in energy, power and latency. In this work, we study a theoretical model to determine the fundamental limits of accuracy and computing time for SCAΣΔM. Since the ΣΔ streams are periodic the final computing error is non-zero and depends on the period of the input streams. We validate our theoretical model with Spice-level simulations and evaluate the power and energy consumption using a standard FinFet1X2 technology for two cases: 1) multiplication and 2) gamma correction, an image processing algorithm. Our work determines circuit design guidelines for SC-AΣΔM and shows that multiplication with SC-AΣΔM requires at least 6X less time than SSC. The latency reduction and novel architecture positively impacts the overall energy consumption in the IoT node, enabling savings in energy of 79% compared with the binary approach.

Aeronautical communications are expected to increasingly demand spectrum in the next years. Given the endemic scarcity of spectrum, both the opportunistic use of licensed bands and carrier aggregation enable aeronautical systems to accommodate higher data rates and more aircrafts. We study dynamic spectrum allocation for air-to-ground (A2G) transmissions when carriers can be aggregated to form larger channels with complete and incomplete information: the aircrafts might not reveal their available channels for security reasons as it would expose their location. The single and multiple ground station scenarios are analyzed. Semi-distributed algorithms are proposed to deal with the incomplete information case for both scenarios, exhibiting a very good tradeoff between performance and complexity.

Use of Orthogonal Frequency Division Multiplexing (OFDM) has been popular, especially in wireless channels, due to its ability to perform frequency-domain channel equalization. Estimating channel frequency response is essential to successful data recovery. In this paper, we compare traditional estimation methods using interpolation among pilot measurements to a parametric model (PM)-based channel estimation. This PM-based technique uses the ESPRIT (Estimation of Signal Parameters by Rotational Invariance Techniques) method to estimate time delays of multiple paths in the channel. Then a least-squares estimator is used to estimate the channel frequency response. Though this subspace method is computationally more expensive, experimental results show that it performs much better than traditional interpolation techniques.

We present an optimal frame timing estimator for OFDM signals that utilizes both cyclic prefix (CP) and pilot-carrier-aided channel estimation. Combining the periodic nature of the embedded pilot signal information with the correlation present in the cyclic prefix allows improved frame timing estimates relative to use of either one. Following a derivation of the ML estimator, a processor diagram is provided, and simulation results compare the performance of the new synchronizer with that of Sandell et al [1] that employs only the CP structure. In the present paper, we assume negligible frequency offset due to Doppler and/or oscillator frequency error.

There is a confluence of recent trends involving data center technology, software defined networks (SDN), and network function virtualization (NFV) that may open a way for general purpose networks to support application specific optimization (ASO). While traditional communications protocol architecture mandates layering where the lowest layers are application agnostic, research in cross layer design attests to the inefficiencies inherent in the "dumb pipes" networking paradigm. This paper investigates the potential of significant performance gains possible over the access network by departing from the traditional layered protocol approach and using a software defined protocol in conjunction with subscriber and application partitioning to provide ASO over the access network, while still maintaining a TCP/IP protocol stack to provide connectivity to the rest of the Internet. As a case study, we examine the potential performance gains provided by ASO of video streaming over the ADSL access network.

Communication engineers routinely deal with bandpass signals and systems, in which the frequency ranges of interest are typically a small range located about some high-frequency carrier frequency. For reasons of simpler analysis, simulation, and even hardware development, it is convenient to work with the complex equivalent low-pass responses of such signals and systems. This chapter develops this idea for deterministic and random signals when acted upon by bandpass systems, as well as important ideas in sampling of bandpass signals. Illustrations are provided for some common communication formats.

We study the design of moderate-length discrete-time pulse-shaping filters used in data communications, focusing on the tradeoff between ISI, out-of-band power, and filter length. Oversampling ratio M=2 and 4 is studied for both symmetric and asymmetric impulse responses. Numerical minimization of out-of-band power, subject to constraints on ISI, is our primary tool.

We consider maximizing achievable information rate subject to a transmission mask constraint on power spectral density, with specific attention to two primary transmission strategies: faster than Nyquist (FTN) transmission and OFDM. OFDM is a mature PHY-layer technology, but there has been significant recent interest in faster than Nyquist transmission (see [1]), a single carrier approach that admits significant ISI rather than avoiding it, and for which attainment of the mask-constrained capacity is achievable, given sufficient receiver complexity and alphabet size at the transmitter. While FTN is theoretically interesting it's our view that traditional OFDM, with aggressive design, can more easily attain the capacity implied by the mask.

We study achievable information rates for nonlinear channels with memory, in the context of satellite communication with QAM modulation. The complete channel model can be described by a Volterra expansion, but large alphabet size and/or large channel memory length may prohibit optimal soft-output demodulator processing, say with the BCJR algorithm. Thus we focus on reduced-state receivers and their achievable information rates as a function of state complexity, amplifier backoff, and receiver input sampling rate. These achievable rates for mismatched receivers are known to be attainable with powerful error control codes and optimal decoding.

Bidirectional satellite communication between earth terminals on the same frequency at the same time is an emerging means of doubling spectral efficiency on satellite channels. With a linear satellite repeater, cancellation of self-interference can be done with standard echo cancelling methods. However, satellite amplifiers are normally operated in a highly-nonlinear regime, for maximum power output, and this complicates the interference removal process. This paper studies a particle filter based algorithm for 'inverting' the nonlinearity at the receiving terminal, making the resulting channel roughly linear, so echo cancelation again becomes attractive. The particle filtering approach approximates the MMSE estimate of the input signal, given the output sequence. This output sequence is followed by a matched filter and an adaptive echo canceller to remove the co-channel interference.

Two-way amplify-and-forward relaying between earth terminals with both users sharing the same bandwidth offers an improvement in spectral efficiency of 100%, relative to traditional frequency-multiplexing, without increase in downlink resources. This co-existence is possible due to the side-information retained in each receiver about its own ‘echo’ signal. While this has been widely studied in the context of linear relaying, two-way amplify/forward on a nonlinear satellite channel raises additional questions, dealing with synchronization to allow mitigation of self-interference; the achievable information rates and optimal amplifier backoff; and the performance of a ‘real’ two-way system in the context of DVB-S2 coding and modulation.

This issue of the magazine is dedicated to electrical safety. The author has been asked to outline some of the advancements in the standards that have resulted from the IEEE Industry Applications Society (IAS) Electrical Safety Workshop (ESW). Over the years, the ESW has provided this networking opportunity for attendees working on better and safer ways to work for other organizations such as the ...