A New Error Control Scheme for Hybrid ARQ Systems

Krishna, Hari; Morgera, S.D.

doi:10.1109/tcom.1987.1096688

Cited by 57 publications

(17 citation statements)

References 13 publications

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“…Two main combining strategies have been proposed, namely Chase combining [60] [44] generalized the Type-II HARQ schemes based on a new class of linear codes, whose encoder/decoder configuration does not change as the length of the code is varied. Morgera et al 1989 [45] employed soft-decision decoding in generalized HARQ schemes.…”

Section: B Combining Transmissionsmentioning

confidence: 99%

A Survey and Tutorial on Low-Complexity Turbo Coding Techniques and a Holistic Hybrid ARQ Design Example

Chen

Maunder

Hanzo

2013

IEEE Commun. Surv. Tutorials

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Abstract-Hybrid Automatic Repeat reQuest (HARQ) has become an essential error control technique in communication networks, which relies on a combination of arbitrary error correction codes and retransmissions. When combining turbo codes with HARQ, the associated complexity becomes a critical issue, since conventionally iterative decoding is immediately activated after each transmission, even though the iterative decoder might fail in delivering an error-free codeword even after a high number of iterations. In this scenario, precious battery-power would be wasted. In order to reduce the associated complexity, we will present design examples based on Multiple Components Turbo Codes (MCTCs) and demonstrate that they are capable of achieving an excellent performance based on the lowest possible memory octally represented generator polynomial (2, 3)o. In addition to using low-complexity generator polynomials, we detail two further techniques conceived for reducing the complexity. Firstly, an Early Stopping (ES) strategy is invoked for curtailing iterative decoding, when its Mutual Information (MI) improvements become less than a given threshold. Secondly, a novel Deferred Iteration (DI) strategy is advocated for the sake of delaying iterative decoding, until the receiver confidently estimates that it has received sufficient information for successful decoding. Our simulation results demonstrate that the MCTC aided HARQ schemes are capable of significantly reducing the complexity of the appropriately selected benchmarkers, which is achieved without degrading the Packet Loss Ratio (PLR) and throughput. codes. Figure 1.1 of [1] outlines the brief history of FEC codes. The ratio of the number of information bits to the total number of information and parity bits defines the normalized throughput or the coding rate. Shannon's channel capacity determines the upper bound of the coding rate that any FEC code may be able to achieve at a certain Signal Noise Ratio (SNR). Since the transmission of these parity bits requires an increased bandwidth, the maximum coding rate that an FEC code can have, while still recovering the information bits becomes a useful criterion for quantifying the capability of FEC codes. Their decoding complexity is also a critical factor in the evaluation of FEC codes. Researchers have studied the associated tradeoff between these two aspects, when choosing a specific FEC code for a communication system. I. TURBO CODING COMPLEXITY A. Turbo Code ComplexityAs one of the most powerful codes in the FEC family, turbo codes [4] have shown capacity-achieving capability by combining two parallel concatenated Recursive Systematic Convolutional (RSC) codes at the transmitter. At the receiver, iterative exchange of soft information is carried out between the two so-called Bahl, Cocke, Jelinek and Raviv (BCJR) decoders [5]. The BCJR decoder is also often referred to as the Maximum A posteriori (MAP) algorithm, which estimates a decoded bit by selecting the specific transition path having the maximum a posteriori pr...

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Section: B Combining Transmissionsmentioning

confidence: 99%

A Survey and Tutorial on Low-Complexity Turbo Coding Techniques and a Holistic Hybrid ARQ Design Example

Chen

Maunder

Hanzo

2013

IEEE Commun. Surv. Tutorials

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“…Code combining was first discussed in a 1985 paper by Chase [91], who coined the term. Subsequent code-combining systems are exemplified by the work of Krishna, Morgera, and Odoul [92], [93]. An early version of a code-combining system was the type-II hybrid-ARQ protocol invented by Lin and Yu [94].…”

Section: E Hybrid-arq Protocols and Packet Combiningmentioning

confidence: 99%

Applications of ErrorControl Coding

VerdÂ¹,

McLaughlin²

2009

Information Theory

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Abstract-An overview of the many practical applications of channel coding theory in the past 50 years is presented. The following application areas are included: deep space communication, satellite communication, data transmission, data storage, mobile communication, file transfer, and digital audio/video transmission. Examples, both historical and current, are given that typify the different approaches used in each application area. Although no attempt is made to be comprehensive in our coverage, the examples chosen clearly illustrate the richness, variety, and importance of error-control coding methods in modern digital applications.

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“…Since each of the blocks is a code of small dimension and distance, as compared to the dimension and distance of the original code, we can examine these codes further to simplify the design of the decoder for these blocks. For example, the small (3,2,2), (6,3,3) and (9,4,4) codes are one-step majority logic decodable, and this fact can be incorporated into the design of the decoder for the blocks. The decoder configuration is such that it can be implemented using a high speed parallel architecture.…”

Section: Theorem 5 If the Number Of Errors That Take Place In A Codementioning

confidence: 99%

“…From the (24, 6, 9) code, we can obtain the (21, 6, 7) code by dropping any one of the 4 blocks (having 3 columns each) C 1 , C2, C3, or C 6 from the generator matrix of the (24, 6, 9) code. Using similar techniques, we can obtain the generator matrices for the (18,6,6), (15,6,4), and (12, 6, 3) codes by discarding suitable blocks from the generator matrix of C of the (24, 6, 9) code. Step 4 of the procedure, the reconstruction for a subset S,, is disabled if the subset S,, has any of the decoder outputs corresponding to the blocks {C~} as input.…”

Section: Lemma 2 If a Block Of Length Nj Corresponding To The Computmentioning

confidence: 99%

On a signal processing algorithms based class of linear codes

Krishna

1993

AAECC

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Abstract. In this work, the correspondence between linear (n,k,d) codes and aperiodic convolution algorithms for computing a system 05 of k bilinear forms over GF(p") is explored. A number of properties are established for the linear codes that can be obtained from a computational procedure of this type. A particular bilinear form is considered and a class of linear codes over GF(2 m) is derived with varying k and d parameters. The code length n is equal to the multiplicative complexity of the computation of an aperiodic convolution and an efficient computation thereof leads to the shortest codes possible using this approach, many of which are optimal or near-optimal. A new decoding procedure for this class of linear codes is presented which exploits the block structure of the generator matrix of the codes. Several interesting observations are made on the nature of the codes obtained as a result of such computations. Such a computation of bilinear forms can be generalized to include other bilinear forms and the related classes of codes.

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A New Error Control Scheme for Hybrid ARQ Systems

Cited by 57 publications

References 13 publications

A Survey and Tutorial on Low-Complexity Turbo Coding Techniques and a Holistic Hybrid ARQ Design Example

A Survey and Tutorial on Low-Complexity Turbo Coding Techniques and a Holistic Hybrid ARQ Design Example

Applications of ErrorControl Coding

On a signal processing algorithms based class of linear codes

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