We propose a novel causal coding scheme with forward error correction (FEC) for a point-to-point communication link with delayed feedback. The proposed model can learn the erasure pattern in the channel, and adaptively adjust its transmission and FEC rate based on the burstiness of the channel and the feedback. We investigate the throughput, and the in-order delivery delay of the adaptive causal coding algorithm, and contrast its performance with the one of the selective repeat (SR) ARQ. We demonstrate via an experimental study of the protocol that our model can double the throughput gains, and triple the gain in terms of mean in-order delivery delay when the channel is bursty, while keeping the difference between the maximum and mean in-order delivery delay is much smaller than SR ARQ. Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications applications. We validate the performance of data delivery under the traces of Intel.
Systematic codes have been proposed in @cite_6 , which are coded generalizations of selective repeat ARQ, and the adaptive coded ARQ model with cumulative feedback as in @cite_5 .
@cite_5 @cite_6
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Current approaches to the practical implementation of network coding are batch-based, and often do not use feedback, except possibly to signal completion of a file download. In this paper, the various benefits of using feedback in a network coded system are studied. It is shown that network coding can be performed in a completely online manner, without the need for batches or generations, and that such online operation does not affect the throughput. Although these ideas are presented in a single-hop packet erasure broadcast setting, they naturally extend to more general lossy networks which employ network coding in the presence of feedback. The impact of feedback on queue size at the sender and decoding delay at the receivers is studied. Strategies for adaptive coding based on feedback are presented, with the goal of minimizing the queue size and delay. The asymptotic behavior of these metrics is characterized, in the limit of the traffic load approaching capacity. Different notions of decoding delay are considered, including an order-sensitive notion which assumes that packets are useful only when delivered in order. Our work may be viewed as a natural extension of Automatic Repeat reQuest (ARQ) schemes to coded networks. This study proposes a methodology to support coding professionals in assigning ICD-9-CM codes to inpatient episodes. This subject has been predominantly addressed through the use of natural language processing methods, which show limited generalizability. To surpass this issue, this paper proposes a methodology entailing an adaptive data processing method based on structured electronic health record data, whereby raw clinical data is mapped into a feature set, and based on which supervised learning algorithms are trained. After applying a filter method for feature selection, support vector machine (SVM) classifiers are trained to obtain predictions for assigning codes to each episode. This approach is tested using a dataset of inpatient episodes from a department of Internal Medicine. Classifiers exhibited F1-measure values around 52 . Recall was generally higher than precision, which is considered valuable for coding support purposes. Analyzing results on an individual code basis sheds light on some key-issues regarding the use of structured electronic health record data in supporting clinical coding. This paper investigates Automatic Repeat request (ARQ) designs for Physical-layer Network Coding (PNC) systems. Most prior work related to PNC explores its use in Two-Way Relay Channel (TWRC). We have previously found that, besides TWRC, there are many other PNC building blocks—building blocks are simple small network structures that can be used to construct a large network. In some of these PNC building blocks, the receivers can obtain side information through overhearing. Although such overheard information is not the target information that the receivers desire, the receivers can exploit the overheard information together with a network-coded packet received to obtain a desired native packet. This can yield substantial throughput gain. Our previous study, however, assumed what is sent always gets received. In practice, that is not the case. Error control is needed to ensure reliable communication. This paper focuses on ARQ designs for ensuring reliable PNC communication. The availability of overheard Information and its potential exploitation make the ARQ design of a network-coded system different from that of a non-network-coded system. In this paper, we lay out the fundamental considerations for such ARQ designs: 1) we put forth a framework to track the stored coded packets and overheard packets to increase the chance of packet extraction, and derive the throughput gain achieved therefore; 2) we investigate two variations of PNC ARQ, coupled and non-coupled ARQs, and prove that non-coupled ARQ is more efficient; 3) we show how to optimize parameters in PNC ARQ—specifically the window size and the ACK frequency—to minimize the throughput degradation caused by ACK feedback overhead and wasteful retransmissions due to lost ACK. Multiple antennas at both the transmitter and receiver ends of a wireless digital transmission channel may increase both data rate and reliability. Reliable high rate transmission over such channels can only be achieved through Space-Time coding. Rank and determinant code design criteria have been proposed to enhance diversity and coding gain. The special case of full-diversity criterion requires that the difference of any two distinct codewords has full rank. Extensive work has been done on Space–Time coding, aiming at finding fully diverse codes with high rate. Division algebras have been proposed as a new tool for constructing Space–Time codes, since they are non-commutative algebras that naturally yield linear fully diverse codes. Their algebraic properties can thus be further exploited to improve the design of good codes. The aim of this work is to provide a tutorial introduction to the algebraic tools involved in the design of codes based on cyclic division algebras. The different design criteria involved will be illustrated, including the constellation shaping, the information lossless property, the non-vanishing determinant property, and the diversity multiplexing trade-off. The final target is to give the complete mathematical background underlying the construction of the Golden code and the other Perfect Space–Time block codes.