Hard-decision Demodulation Research Articles

Soft Decisions of D-PSK Demodulation for G3 OFDM Technology

G3-PLC, an orthogonal frequency division multiplexing (OFDM) power line communication solution, has recently gained a lot of attention. It supports the application of four types of baseband mapping modes in different environments. These modes typically require a hard-decision demodulation, which will lead to nearly 3dB preference loss. In this paper, we propose an improvement scheme for the baseband mapping modes by changing the constellation encoding method. The optimal soft decision algorithm which makes use of log likelihood ratio (LLR) of the probabilities is used in the demodulators. Simulation results show that the proposed scheme can outperformer previous algorithm.

On the Equivalence Between Maximum Likelihood and Minimum Distance Decoding for Binary Contagion and Queue-Based Channels with Memory

We study the optimal maximum likelihood (ML) block decoding of general binary codes sent over two classes of binary additive noise channels with memory. Specifically, we consider the infinite and finite memory Polya contagion and queue-based channel models, which were recently shown to approximate well binary modulated correlated fading channels used with hard-decision demodulation. We establish conditions on the codes and channels parameters under which ML and minimum Hamming distance decoding are equivalent. We also present results on the optimality of classical perfect and quasi-perfect codes when used over the channels under ML decoding. Finally, we briefly apply these results to the dual problem of syndrome source coding with and without side information.

MAP Detection and Robust Lossy Coding Over Soft-Decision Correlated Fading Channels

The joint source-channel coding (JSCC) problem for soft-decision-demodulated time-correlated fading channels is investigated without the use of channel coding and interleaving. For the purpose of system design, the recently introduced nonbinary noise discrete channel with queue-based (QB) noise (NBNDC-QB) is adopted. This analytically tractable Markovian model has been shown to represent effectively correlated fading channels that are hard to handle analytically. Optimal sequence maximum a posteriori (MAP) detection of a discrete Markov source sent over the NBNDC-QB is first studied. When the Markov source is binary and symmetric, a necessary and sufficient condition under which the MAP decoder is reduced to a simple instantaneous symbol-by-symbol decoder is established. Two robust lossy source coding schemes with a low encoding delay are next proposed for the NBNDC-QB. The first scheme consists of a scalar quantizer (SQ), a proper index assignment, and a sequence MAP decoder designed to harness the redundancy left in the indexes of the quantizer and the soft-decision output and the noise correlation of the channel. The second scheme is a classical noise-resilient vector quantizer known as the channel-optimized vector quantizer (COVQ). It is demonstrated that both systems can successfully exploit the memory and soft-decision information of the channel. Signal-to-distortion-ratio (SDR) gains of more than 1.7 dB are obtained over hard-decision demodulation by using only two bits for soft decision. Furthermore, gains as high as 4.4 dB can be achieved for a strongly correlated channel, in comparison with systems designed for the ideally interleaved (memoryless) channel. Finally, it is numerically observed that, for low coding rates, the NBNDC-QB model can accurately approximate discrete fading channels (DFCs) in terms of SDR performance.

Improved Baseband Mapping Method for G3 OFDM Technology

G3-PLC, an orthogonal frequency division multiplexing (OFDM) power line communication solution, has recently gained a lot of attention. It supports the application of four types of baseband mapping modes in different environments. These modes typically require a hard-decision demodulation, which will lead to nearly 3dB preference loss. In this paper, we propose an improvement scheme for the baseband mapping modes by changing the constellation encoding method. The optimal soft decision algorithm which makes use of log likelihood ratio (LLR) of the probabilities is used in the demodulators. Simulation results show that the proposed scheme can outperformer many existing algorithms.

A Discrete Queue-Based Model for Capturing Memory and Soft-Decision Information in Correlated Fading Channels

A discrete (binary-input 2q-ary output) communication channel with memory is introduced to judiciously capture both the statistical memory and the soft-decision information of a time-correlated discrete fading channel (DFC) used with antipodal signaling and soft output quantization of resolution q. The discrete channel, which can be explicitly described via its binary input process and a 2q-ary noise process, is shown to be symmetric, thus admitting a simple expression for its capacity when its noise is stationary ergodic. It is observed that considerable capacity gains can be achieved due to the channel's memory and the use of as few as 2 bits for soft-decision over interleaving the channel (to render it memoryless) and hard-decision demodulation (q=1). The 2q-ary noise process is next modeled via a queue-based (QB) ball-sampling mechanism to produce a mathematically tractable stationary ergodic Markovian noise source. The DFC is fitted by the QB noise model via an iterative procedure that minimizes the Kullback-Leibler divergence rate between the DFC and QB noise sources. Modeling results, measured in terms of channel noise correlation function and capacity reveal a good agreement between the two channels for a broad range of fading conditions.

Packet-Based Modeling of Reed–Solomon Block-Coded Correlated Fading Channels Via a Markov Finite Queue Model

We consider the transmission of a Reed-Solomon (RS) code over a binary modulated time-correlated flat Rician fading channel with hard-decision demodulation. We define a binary packet (symbol) error sequence that indicates whether an RS symbol is successfully transmitted across the discrete (fading) channel whose input enters the modulator and whose output exits the demodulator. We then approximate the packet error sequence of the discrete channel (DC) using the recently developed queue-based channel (QBC), which is a simple finite-state Markov channel model with <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> th-order Markovian additive noise. In other words, we use the QBC to model the binary DC at the packet level. We propose a general framework for determining the probability of codeword error (PCE) for QBC models. We evaluate the modeling accuracy by comparing the simulated PCE for the DC with the numerically evaluated PCE for the QBC. Modeling results identify accurate low-order QBC models for a wide range of fading conditions and reveal that modeling the DC at the packet level is an efficient tool for nonbinary coding performance evaluation over binary channels with memory.

Benefits of Spatial Correlation for Multi-Antenna Non-Coherent Communication over Fading Channels at Low SNR

For fading channels without channel state information (CSI) at the transmitter or the receiver, fundamental challenges arise for realizing efficient communication, especially under stringent constraints on average and peak input powers. To mitigate these challenges, in this paper we investigate the benefits of spatial correlation among multiple transmit and receive antennas. Based upon asymptotic analyses, we first show that spatially correlated antennas lead to both multiplicative rate gain as well as peak power reduction, at no cost of additional transmit power. Then we turn to a simple communication scheme employing on-off signaling with hard-decision demodulation. For this low-complexity scheme, we demonstrate that most of the benefits promised by the asymptotic analyses are realizable

Soft multiuser demodulation and iterative decoding for FH/SSMA with a block turbo code

The number of users that can be supported by frequency-hopped, spread-spectrum multiple-access systems can be increased greatly by using multiuser demodulation and iterative decoding. In the receiver employed hard-decision multiuser demodulation followed by iterative decoding, users exchange decoded information with each other. Additional information from multiuser demodulation in the first decoding iteration is limited by the hard-decision output of the multiuser demodulator. The error-correction used was an errors-and-erasures Reed-Solomon (RS) decoder. We revisit hard-decision demodulation and conventional RS decoding. Hard-decision multiuser demodulation is modified to provide a soft output, which is then given to a nonbinary block turbo code with shortened RS codes as the constituent codes. An iterative multiuser decoding algorithm is developed to do soft multiuser interference cancellation. This soft receiver with soft demodulation and decoding is shown to be more resistant to multiuser interference and channel noise, especially at lower values of signal-to-noise ratio. The results show a great improvement in the ability of the system to support more users (more than three times in some cases), as compared with systems that erase all hits or employ hard-decision multiuser demodulation followed by RS code. We examine the proposed method for synchronous as well as asynchronous frequency-hopped systems in both AWGN and fading channels.

Soft-decision demodulation design for COVQ over white, colored, and ISI Gaussian channels

In this work, the design of a q-bit (scalar and vector) soft-decision demodulator for Gaussian channels with binary phase-shift keying modulation is investigated. The demodulator is used in conjunction with a soft-decision channel-optimized vector quantization (COVQ) system. The COVQ is constructed for an expanded (q>1) discrete channel consisting of the concatenation of the modulator, the Gaussian channel, and the demodulator. It is found that as the demodulator resolution q increases, the capacity of the expanded channel increases, resulting in an improvement of the COVQ performance. Consequently, the soft-decision demodulator is designed to maximize the capacity of the expanded channel. Three Gaussian channel models are considered as follows: (1) additive white Gaussian noise channels; (2) additive colored Gaussian noise channels; and (3) Gaussian channels with intersymbol interference. Comparisons are made with (a) hard-decision COVQ systems, (b) COVQ systems which utilize interleaving, and (c) an unquantized (q=/spl infin/) soft-decision decoder proposed by Skoglund and Hedelin (1999). It is shown that substantial improvements can be achieved over COVQ systems which utilize hard decision demodulation and/or channel interleaving. The performance of the proposed COVQ system is comparable with the system by Skoglund and Hedelin-though its computational complexity is substantially less.

Erasure insertion in frequency-hop communications with fading and partial-band interference

The use of block coding and errors-and-erasures decoding can enhance performance substantially in frequency-hop communication systems, provided that a good scheme is employed to determine which symbols to erase. In this paper, methods for determining erasures derived from Bayesian decision theory are applied to the mitigation of fading and partial-band interference. The performance of receivers using the Bayesian technique is compared with that of receivers that make erasure decisions using Viterbi's (1982) ratio-threshold test. The performance of hard-decision demodulation and the theoretical performance of receivers with access to perfect side information are also compared. It is found that the Bayesian receiver provides the best performance, and that error probabilities for the Bayesian receiver are lower than those for hard-decision demodulation by as much as six orders of magnitude.

On the Coding Gain of Linear Binary Block Codes

The coding gain of linear binary block codes on the AWGN channel is studied. Antipodal signaling and hard decision demodulation are assumed. Simple asymptotic expressions for the gain at high and low energy to noise spectral density ratios are derived. Monotonicity of the coding gain is also discussed.

Soft Decision Demodulation for PCM Encoded Speech Signals

The effect of digital errors in PCM encoded speech signals transmitted over a noisy channel is reduced by using soft decision demodulation at the receiver. The reliability information supplied by the soft decision demodulator is used to point out likely transmission errors, especially in the most significant PCM bits. When a likely transmission error is identified, the corresponding PCM word is rejected by the receiver and replaced by a predictor estimate or an interpolation estimate if delayed decisions are used. We have analyzed soft decision demodulation schemes for standard PCM encoded speech signals transmitted over the Gaussian channel with coherent PSK (phase shift keying). A signal to noise ratio gain in E_{b}/N_{0} of the order of 1-2 dB is Obtained at low input signal levels. The gain depends on the performance of the predictor or, alternatively, the interpolator. No modifications of the transmitter are required to obtain this improvement. The suggested soft decision schemes are optional at the receiver. The comparisons are made with hard decision demodulation.