Chase-Like Decoding of Arithmetic Codes with Applications

Motivated by recent results in Joint Source/ Channel (JSC) coding and decoding, this paper addresses the problem of soft input decoding of Arithmetic Codes (AC). A new length-constrained scheme for JSC decoding of these codes is proposed based on the Maximum a posteriori (MAP) sequence estimation criterion. The new decoder, called Chase-like arithmetic decoder is supposed to know the source symbol sequence and the compressed bit-stream lengths. First, Packet Error Rates (PER) in the case of transmission on an Additive White Gaussian Noise (AWGN) channel are investigated. Compared to classical arithmetic decoding, the Chase-like decoder shows significant improvements. Results are provided for Chase-like decoding for image compression and transmission on an AWGN channel. Both lossy and lossless image compression schemes were studied. As a final application, the serial concatenation of an AC with a convolutional code was considered. Iterative decoding, performed between the two decoders showed substantial performance improvement through iterations.

This paper presents asymptotic multiuser efficiency (AME) performance analysis of the decorrelator based successive interference cancellation (DBSIC) DS-CDMA multiuser receiver DBSIC is similar to the conventional SIC receiver except that a decorrelator is used at each detection stage prior to cancellation. AMEs of DBSIC are compared with those of single-user matched filter, optimum, decorrelating and conventional SIC receivers over both additive white Gaussian noise (AWGN) and Rayleigh fading channels. It is shown that over AWGN channels, DBSIC AME is lower than the optimum receiver AME when the interfering user is weaker than the user of interest but approaches the unity optimum receiver AME as the interferer becomes stronger than the user of interest. For all spreading codes cross-correlation considered, DBSIC has a similar AME curve shape as the conventional SIC receiver but has a higher AME which remains positive for all user energy ratios, illustrating its near-far resistance over AWGN channels. The AME of DBSIC is better than that of the decorrelating detector when the interferer is much weaker or slightly stronger than the user of interest and has worse performance when the interferer is not much weaker. It is shown that DBSIC is completely near-far resistant over Rayleigh fading channels with the same AME as the decorrelating scheme for user 1 and as the optimum scheme for user 2, both AMEs being independent of the user energy ratio. This shows that DBSIC is preferable compared to the decorrelating detector, while still being less complex than the optimum scheme over Rayleigh fading channels

This correspondence analyzes the performance of concatenated coding systems and modulation schemes operating over the additive white Gaussian noise (AWGN) channel by examining the loss of capacity resulting from each of the processing steps. The techniques described in this correspondence allow the separate evaluation of codes and decoders and thus the identification of where loss of capacity occurs. Knowledge of this capacity loss is very useful for the overall design of a communications system, e.g., for evaluating the benefits of inner decoders that produce information beyond the maximum-likelihood (ML) estimate. The first two sections of this correspondence provide a general technique for calculating the composite capacity of an orthogonal or a bi-orthogonal code and the AWGN channel in isolation. The later sections examine the composite capacities of an orthogonal or a bi-orthogonal code, the AWGN channel, and various inner decoders including the decoder estimating the bit-by-bit probability of a one, as is used in turbo codes. The calculations in these examples show that the ML decoder introduces a large loss in capacity. Much of this capacity loss can be regained by using only slightly more complex inner decoders, e.g., a detector for M-ary frequency-shift keying (MFSK) that puts out the two most likely frequencies and the probability the ML estimate is correct produces significantly less degradation than one that puts out only the most likely frequency.

Modulo lattice additive noise (MLAN) channels appear in the analysis of structured lattice codes with lattice decoding for Costa's dirty-paper channel and the additive white Gaussian noise (AWGN) channel. Building on the recent result on the optimal density of an infinite constellation over an AWGN channel, in this paper, it is shown that with a proper choice of the shaping lattice and the scaling parameter, the dispersion of the MLAN channel is asymptotically the same as that of the (zero-interference) AWGN channel at the same signal-to-noise ratio.

In this paper, we introduce Hyper-Dimensional Modulation (HDM) for massive machine-type communications (mMTC). HDM enables robust communication of short packets by spreading information bits across many elements in a hyper-dimensional vector and superimposing a set of such non-orthogonal vectors. The proposed CRC-aided K-best decoding algorithm for HDM can achieve a very low packet error rate (PER) in additive white Gaussian noise (AWGN) channels for short packets. Furthermore, extended decoding algorithms are proposed to combat overwhelming interference in an mMTC network. Comprehensive simulation and real-world experiment results show that HDM outperforms sparse superposition codes in AWGN channels and state-of-the-art short codes such as polar and tail-biting convolutional codes in interference-heavy channels for short packet transmissions.

It is well known that binary error-correcting codes with iterative decoders can achieve near Shannon-limit performance on the additive white Gaussian noise (AWGN) channel, but their performance on more realistic wireless channels can become degraded due to the presence of burst errors or impulsive noise due to interference. A better performing coding scheme is the class of non-binary codes, which are known to be more effective in correcting burst errors, but interestingly there is no research reported in the literature investigating non-binary codes on impulsive noise channels. In this paper, we investigate the performance of non-binary turbo codes defined in a finite field GF(4) on symmetric alpha-stable impulsive noise channels and compare with comparable binary turbo codes. A Cauchy receiver is also employed to mitigate the effects of the channel to assist the turbo decoding. Our simulation results show that although the non-binary turbo code performs similarly to the binary turbo code on the AWGN channel, it achieves a significant coding gain over the binary turbo code as impulsiveness increases.

This paper investigates an iterative multiuser detection for nonbinary low density parity check (LDPC) coded multicarrier multiple level frequency shift keying system to increase system performance under specific signal-to-noise ratio and data rate. We propose three-level hard-limited detection probabilities over both additive white Gaussian noise (AWGN) channels and Rayleigh fading channels. During multiuser detection (MUD) process, the hard-limited detection probabilities are computed in advanced and stored in tables. By using table looking up, the MUD soft outputs can be computed efficiently. We test the reliability of soft outputs from nonbinary LDPC channel decoder for all users. If the soft output exceeds a reliability threshold, the user is declared as a reliable user. For each symbol, we count the number of reliable users on it, and, use this information to update the soft output of MUD during the iterative multiuser detection and decoding process, which cancel multiple access interference iteratively. Numerical results show that the performances of three-level hard-limited systems outperform two-level hard-limited systems over AWGN channels and Rayleigh fading channels.

Semialgebraic low-density parity-check (SA-LDPC) codes are proposed for the multilevel coded modulation system. We optimize code parameters of LDPC codes according to the rate of each level by Gaussian approximation. Iterative multistage decoding (IMSD) scheme is adopted to get the significant improvement. System performance with Ungerboeck partitioning (UP) and mixed partitioning (MP) for 8PSK is evaluated respectively over additive white Gaussian noise (AWGN) channels. Many results are presented, they indicate that in terms of the tradeoff between hardware complexity and system performance, constructed multilevel coded modulation system based on optimized LDPC codes, capacity rule and MP is a good choice for the bandwidth efficient transmission over AWGN channels.

Multiple trellis coded modulation of constant envelope frequency and phase modulated signal sets (MTCM/FPM) is investigated for performance on the additive white Gaussian noise (AWGN) channel and on the one-sided normal, Rayleigh and Rician fading channels. The Nakagami-m fading model is used as an alternative to the Rician fading model to calculate the error probability upper bound for trellis-coded schemes on the fading channel. The likeliness and the disparity between the upper bounds to the error probability for the two fading models are discussed. The design criteria for the one-sided normal fading channel, modeled by the Nakagami-m distribution, are observed to be the same as those for the Rayleigh-fading channel. For the MTCM/FPM schemes, it is demonstrated that the set partitioning designed to maximize symbol diversity (optimum for fading channels) is optimum for performance on the AWGN channel as well. The MTCM/FPM schemes demonstrate improved performance over MTCM/MPSK schemes and TCM/FPM schemes on the AWGN channel and the fading channel.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Recently, the differential detection scheme has attracted considerable attention as a demodulated scheme for digital mobile communications because of its robustness in the frequency nonselective fading channel. A problem of the differential detection scheme is that its bit error rate (BER) performance in the additive white Gaussian noise (AWGN) channel is inferior to that of the coherent detection scheme. To solve this problem, many methods to improve BER performance of the differential detection in the AWGN channel have been proposed. However, those methods require complex signal processings.This paper proposes a novel differential detection scheme as a simpler improvement method which estimates the differential phase of the transmitted signal by a sequence estimation scheme using the Viterbi algorithm. The proposed scheme is simplified in a manner such that its signal processing is composed of only additions and subtractions on the phase information of the received signal. Results of computer simulation show that BER performance of the proposed scheme is close to that of the ideal coherent detection in the AWGN channel. In addition, the trellis diagram of the Viterbi algorithm can be reduced without performance degradation introducing the signal processing similar to the Scarece State Transition (SST) type Viterbi decoding. The proposed scheme also is useful in the case of the fast Rician fading channel and the slow Rayleigh fading channel.

The rateless multiple access (RMA) scheme is a promising distributed multiple access scheme to achieve simultaneous high reliability, low latency and massive connectivity. In this paper, we investigate the maximum likelihood (ML) decoding performance of the RMA scheme in an Additive white Gaussian noise (AWGN) channel with binary phase-shift keying (BPSK) modulation. For the first time, this paper derives the ensemble weight distribution of the RMA scheme. We derive an upper bound on the decoding error performance of the RMA scheme under ML decoding in an AWGN channel with BPSK modulation. Using the derived bound as the fitness function, we adopt the continuous genetic algorithm to optimize the parameters of the RMA scheme. Simulation results show the tightness of the derived bound and the superiority of the optimized degree distribution over the conventional degree distributions.

This paper is concerned with tele‐presence and tele‐operation of autonomous vehicles over the Additive White Gaussian Noise (AWGN) channel. This wireless communication channel is subject to transmission noise and transmission power constraint. An encoder, decoder and controller are proposed by implementing a novel linearization method for linearizing the nonlinear dynamic systems at operating points. For the linearized systems, the encoder, decoder and controller are implemented that were previously proposed for output tracking as well as stability of linear dynamic systems. Two novel linearization methods are proposed and their satisfactory performances are proved for output tracking as well as stability of nonlinear dynamic system. The first method is based on the fixed linearization rate and the second one is based on the variable (optimal) linearization rate. The decoder that is based on the second method is in fact the extended Kalman filter with the optimal linearization rate. The performances of these two methods are compared with each other and the other proposed methods by implementing them to the problems of the tele‐presence and tele‐operation of autonomous vehicles over the AWGN channel. Their satisfactory performances are illustrated. It is illustrated that the second method has higher computational complexity with slightly better performance and is applicable to a larger class of reference trajectories.

We consider the additive white Gaussian noise (AWGN) channel with a (σ, ρ)-power constraint, which is motivated by energy harvesting communication systems. This constraint imposes a limit of σ + kρ on the total power of any k ≥ 1 consecutive transmitted symbols in a codeword. We analyze the capacity of this channel geometrically, by considering the set S n (σ, ρ) ⊆ ℝn which is the set of all n-length sequences satisfying the (σ, ρ)-power constraints. For a noise power of ν, we obtain an upper bound on capacity by considering the volume of the Minkowski sum of S n (σ, ρ) and the n-dimensional Euclidean ball of radius √nν. We analyze this bound using a result from convex geometry known as Steiner's formula, which gives the volume of this Minkowski sum in terms of the intrinsic volumes of S n (σ, ρ). We show that as n increases, the logarithms of the intrinsic volumes of {S n (σ, ρ)} converge to a limit function under an appropriate scaling. An upper bound on capacity is obtained in terms of the limit function, thus pinning down the asymptotic capacity of the (σ, ρ)-power constrained AWGN channel in the low-noise regime. We derive stronger results when σ = 0, corresponding to the amplitude-constrained AWGN channel.

Coding for the fading channel: a survey

This paper presents a new study in an attempt to apply Fast Euclidean Direction Search (FEDS) algorithm on adaptive smart antennas. The novelty in this work is the use of FEDS algorithm in a smart antenna system for mobile communications because up to our knowledge this algorithm is not applied on smart antenna so far. In order to properly evaluate the performance of smart antenna for mobile communication systems, an Additive White Gaussian Noise (AWGN) channel model is required that each received signal at each element in the array includes only an additive, zero mean, Gaussian noise . The ability of the FEDS algorithm to operate in a fast changing signal environment is examined by subjecting the input signal to Rayleigh fading with a Jakes power spectral density which is a popular choice for land mobile communications systems. Through simulation results of smart antennas for AWGN channel, the RLS and FEDS start to converge from the initial iteration and 10 respectively, whereas, the LMS and NLMS start to converge after 50 and 10 iterations respectively. In the presence of the Rayleigh fading channel, the LMS, and NLMS algorithms converge after 60 and 25 iterations respectively, while the RLS convergence from the initial iteration and FEDS converge from the iteration number 25. On the other hands, the FEDS algorithm shows better tracking and estimation of the desired input signal compared with both LMS and NLMS algorithms and comparable with RLS algorithm. The comparison of linear plot of array factor using FEDS and RLS , both algorithms generates the same deeper null for undesired signals of about í30 dB towards the interferer using an AWGN channel, while it generates deeper null of about -23 dB and -30 dB respectively using the Rayleigh fading channel.