Analysis and design of rate compatible serial concatenated convolutional codes

In this letter, we propose and compare some new rate-compatible serially concatenated convolutional code (SCCC) families. To obtain them, inner coded bits only are punctured. However, and this is the novelty proposed in the letter, the puncturing is not limited to inner parity bits, but extended also to inner systematic bits, thus obtaining high rate SCCCs (i.e., beyond the outer code rate). The two main applications of this technique are its use in hybrid Automatic-Repeat-reQuest/Forward-Error Correction (ARQ/FEC) schemes and to achieve unequal error protection (UEP) of an information sequence.

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An analysis of performance of Serially Concatenated Convolutional Codes (SCCC) is evaluated on Additive White Gaussian Noise model channel, which is used as a basis, and actions of SCCC on Raleigh flat slow and flat fast faded channels are evaluated in this research work. In DCS the SCCC are utilized to reduce the bit error rates. SCCC encoder consists of RSCC. The major thrust is iterative decoding. This research has utilized BCJR and TDA decoding algorithms. This research analyzed SCCC with interleaved scheme. The BPSK modulation was considered. Performance metric for SCCC over Memory less AWGN channel, and memory based channels i.e. Rayleigh slow and fast Faded Channel is BER verses SNR.

A coded wideband MC-CDMA system is considered for high-bit-rate data transmission in a typical outdoor environment with Rayleigh multipath fading. First, two powerful interleaved concatenated coding techniques, turbo and serially concatenated convolutional codes (SCCC) codes are applied in the downlink system and important conclusions are derived on their relative performance behavior in this type of system. Simulation results indicate some of the relative merits of SCCC on achieving very low error rates, with relative mitigation of error floor behavior at the typical BER range of interest for wireless data applications. Next, the more critical uplink system is considered, which requires a multiuser detection technique in combination with powerful coding to achieve similar performance. Successive interference cancellation with SCCC coding is presented, with computation of optimal log-likelihood ratios required for this type of interference cancellation followed by SCCC decoding. Application of SCCC coding and interference cancellation has improved the system performance significantly even in the fully loaded case. Based on these results, the combination of SCCC coding and successive cancellation is found to be attractive for high-rate data transmission in the uplink MC-CDMA.

In this paper, we focus on the design of optimized binary convolutional codes (CCs) and serially concatenated convolutional codes (SCCCs) in the presence of a-priori information (API) at the receiver. For large signal-to-noise ratios (SNRs), we first propose a CC design criterion based on the minimization of a union bound on the bit error probability (BEP). In this case, relevant performance gains, with respect to previously proposed CCs, are obtained. These gains persist even in the presence of estimation errors on the API. Then, we apply the same union bound-based design criterion to SCCCs. Since the BEP of SCCCs is characterized by a typical waterfall shape, the proposed union bound-based design criterion is accurate only at large SNR, to estimate the BEP floor. In order to complement this analysis, we propose a density evolution-based approach to optimize the SCCC design in terms of minimization of the SNR of the knee of the BEP curve. The obtained simulation results show substantial gains with respect to previously proposed parallel concatenated convolutional coding (PCCCing) schemes optimized under the assumption of no API at the decoder. Moreover, in the presence of strong API the proposed SCCCs allow to approach the Shannon limit (SL) more than any previously proposed turbo coding scheme.

The paper proposes an analytical method to solve the rate allocation problem in serial concatenated convolutional codes (SCCCs). The goal is to find the best rate allocation between the inner and the outer constituent convolutional codes of an SCCC for constant overall code rate, interleaver size and complexity. Simulation results are shown in the paper to demonstrate the optimum and superior design criteria. In addition, the ‘density evolution’ model is shown to verify the proposed rate allocation method, while indicating that a high rate inner code should not be used for SCCCs. Finally, it is also shown that the upper bounds on BER of ML decoded SCCCs do not provide good design criteria for allocating the rate in iteratively decoded SCCCs.

This paper compares a number of decision feedback schemes that improve the initial channel estimates provided by the pilot symbols alone. The decision feedback scheme that feeds back the systematic bits achieves about the same performance as feeding back both the systematic and parity bits at the low fading rate. Its performance is slightly degraded at the higher fading rate. The advantage of this scheme is its lower complexity as the LLRs of the systematic bits are readily available in the turbo decoding process. Soft decision feedback does not always provide large improvement in performance. Noticeable gain in performance using soft decision feedback is seen only when the bits to be fed back are not reliable during the first few iterations.

This paper considers detection and error control coding for the two-dimensional magnetic recording (TDMR) channel modeled by the two-dimensional (2D) four-rectangular-grain model proposed by Kavcic, Huang et. al. in 2010. This simple model captures the effects of different 2D grain sizes and shapes, as well as the TDMR grain overwrite effect: grains large enough to be written by successive bits retain the polarity of only the last bit written. We construct a row-by-row BCJR detection algorithm that considers outputs from two rows at a time over two adjacent columns, thereby enabling consideration of more grain and data states than previously proposed algorithms that scan only one row at a time. The proposed algorithm employs soft-decision feedback of grain states from previous rows to aid the estimation of current data bits and grain states. Simulation results using the same average coded bit density and serially concatenated convolutional code (SCCC) as a previous paper by Pan, Ryan, et. al. show gains in user bits/grain of up to 6.7% over the previous work when no iteration is performed between the TDMR BCJR and the SCCC, and gains of up to 13.4% when the detector and the decoder iteratively exchange soft information.

When channel state information (CSI) is not available, unitary space-time symbol-based parallel concatenated convolutional code (UST-SB-PCCC) can give a good performance and remain an acceptable calculation complexity, however it also meet with the error floor phenomenon. We propose a scheme utilizing UST-SB serial concatenated convolutional code (SCCC) for multiple-antenna wireless communication systems over rapid fading channels which can avoid the error floor. We also give the corresponding multi-ary MAP decoding algorithm for both the systematic and the parity symbols. With iterative decoding and/or multi-antennas, it can further improve the system performance, which helps to give an acceptable bit error rate (BER).

Objective: The purpose of this paper is to present an overview of the specifications of three guidelines for the seismic design of structures with passive dampers, to compare their similarities, as well as to discuss topics in which each guideline would be desirable to extend. The guidelines compared here are: a) Minimum Design Load for Buildings and Other Structures (ASCE/SEI 7-16), b) European Standard Anti-seismic Devices (EN 15129), and c) Technical Regulations for Seismic Design, corresponding to Mexico City Building Code (NTCS-17). Methods: The document summarizes and discusses the most significant differences and similarities among the three guidelines for the design of structures with energy dissipation devices. The analysis and discussion are focused on the following sections: 1) Type of Dissipation Devices, 2) General Design Requirements, 3) Procedure Selection, 4) Seismic Design Action, 5) Inspection and 6) Testing of Dissipaters. Conclusion: The paper identifies the gaps in each guideline and gives recommendations about its possible extension. The paper concludes that ASCE/SEI 7-16 presents the procedure selection section with more detail; EN 15129 describes with more detail the Testing section, and NTCS-17, the Inspection section. The paper can be useful for engineers and guideline writers from the USA, Europe, Mexico and other countries that are in process of developing their guidelines for structures with supplementary damping.

An iterative detection and decoding (IDD) technique has recently received much attention due to its capacity approaching performance and manageable complexity for (parallel) turbo-coded systems. The existing IDD receivers process indiscriminately the a priori information of the systematic bits and the parity bits generated by the turbo decoder in the front-end detection. In this paper, we first show that the parity bits of the parallel turbo codes are inherently less protected than the systematic bits, which leads to suboptimality for the IDD receivers. Based on this observation, we then propose an unequal-error-correcting-capability-aware technique to mitigate the associated performance loss. As an illustrative example, the minimum-mean-square-error (MMSE) filtering and soft interference cancelation (MMSE-SIC)-aided iterative receiver for parallel-turbo-coded multiple-input-multiple-output (MIMO) systems is employed in this paper. Numerical results manifest that the MMSE-SIC-aided iterative receiver based on the proposed paradigm achieves noticeable performance gains over the conventional unequal-error-correcting-capability-agnostic one even with reduced computational complexity. The extension of the proposed principle to other iterative algorithms for parallel-turbo-coded data transmission is straightforward.

We compare the asymptotic performance of parallel concatenated codes (PCCs) and serial concatenated codes (SCCs) over GF(4). We construct such codes using optimal nonbinary convolutional codes where optimality is in the sense of achieving the largest minimum distance for a fixed number of encoder states. Code rates of the form K/sub 0//(K/sub 0/ + 1) for K/sub 0/ = 1, 8, and 64 are considered. For all of these code rates, we find the minimum distance and its multiplicity for both concatenated code systems. This is accomplished by feeding the encoder with all possible weight-two and weight-three input information patterns and monitoring, at the output of the encoder, the weight of the corresponding codewords and their multiplicity. Our analytical results indicate that the SCC codes outperform their counterpart PCC codes with much lower complexity.

This chapter discusses fundamentals of information theory and channel coding (error correction coding ECC, Forward error correction FEC). First, key results of Shannon, including channel capacity and the relationship between transmit power and bandwidth, are discussed. Block codes multiply a block of data with an encoding matrix. For systematic codes, the resulting codeword consists of systematic bits and parity check bits. Decoding is achieved by multiplication with a parity check matrix and determination of the syndrome vector. Correction of errors within the correction sphere can be done, e.g., through lookup tables. Convolutional codes send the source data stream through shift registers and adders, a process described by a trellis diagram. Maximum-likelihood sequence estimation (Viterbi algorithm) determines the (transmit) bit sequence with best distance metric (Hamming or Euclidean) from the received signal. Methods for combining coding and higher-order modulation include trellis coded modulation (using set partitioning for code design) and bit-interleaved coded modulation (BICM). Turbo codes are close to capacity-achieving. They are based on transmitting differently interleaved convolutional codes; receivers use soft decoding of the constituent codes and iterative exchange of soft information (log-likelihood ratios). Low-density parity check codes (LDPCC) are decoded by belief propagation (message passing), where variable nodes and constraint nodes exchange beliefs about the codeword. In fading channels, (block or convolutional) interleaving is essential to provide diversity. From an information-theoretic point of view, in fading channels we can distinguish between the ergodic capacity and the outage capacity. If the channel state information is known at the transmitter, waterfilling is the optimum power allocation strategy. Automatic Repeat Request ARQ) and Hybrid ARQ (including chase combining or incremental redundancy) are described in the appendix.

In this paper, we derive feedback power control strategies for block-faded multiple access schemes with correlated sources. In particular, upon the derivation of the feasible signal-to-noise ratio (SNR) region for the considered multiple access schemes, i.e., the multidimensional SNR region where error-free communications are, in principle, possible, two feedback power control strategies are proposed: (i) a “classical” feedback power control strategy, which aims at “equalizing” the SNRs at the AP over all communication links, and (ii) an “optimal” feedback power control strategy, which tries to make the network operational point fall in the feasible SNR region at the lowest energy consumption. These strategies will be referred to as balanced SNR and unbalanced SNR, respectively. While they require unlimited power control range at the sources (the sensors), we then propose “practical” implementations by limiting the power control range. We evalute the benefits brought by the use of the proposed feedback power control strategies considering joint channel decoding (JCD) schemes, where the sensors use channel coding and a proper iterative decoding algorithm is considered at the AP. The analysis is carried out considering the use of low-density parity-check (LDPC) codes and a serially concatenated convolutional code (SCCC).

Concatenation is a method of building long codes out of shorter ones, it attempts to meet the problem of decoding complexity by breaking the required computation into manageable segments. Concatenated Continuous Phase Frequency Shift Keying (CPFSK) facilitates powerful error correction. CPFSK also has the advantage of being bandwidth efficient and compatible with non-linear amplifiers. Bandwidth efficient concatenated coded modulation schemes were designed for communication over Additive White Gaussian noise (AWGN), and Rayleigh fading channels. An analytical bounds on the performance of serial concatenated convolutional codes (SCCC), and parallel concatenated convolutionalcodes (PCCC), were derived as a base of comparison with the third category known as hybrid concatenated trellis codes scheme (HCTC). An upper bound to the average maximum-likelihood bit error probability of the three schemes were obtained. Design rules for the parallel, outer, and inner codes that maximize the interleaver's gain were discussed. Finally, a low complexity iterative decoding algorithm that yields a better performance is proposed.