731 research outputs found

    Throughput-based Design for Polar Coded-Modulation

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    Typically, forward error correction (FEC) codes are designed based on the minimization of the error rate for a given code rate. However, for applications that incorporate hybrid automatic repeat request (HARQ) protocol and adaptive modulation and coding, the throughput is a more important performance metric than the error rate. Polar codes, a new class of FEC codes with simple rate matching, can be optimized efficiently for maximization of the throughput. In this paper, we aim to design HARQ schemes using multilevel polar coded-modulation (MLPCM). Thus, we first develop a method to determine a set-partitioning based bit-to-symbol mapping for high order QAM constellations. We simplify the LLR estimation of set-partitioned QAM constellations for a multistage decoder, and we introduce a set of algorithms to design throughput-maximizing MLPCM for the successive cancellation decoding (SCD). These codes are specifically useful for non-combining (NC) and Chase-combining (CC) HARQ protocols. Furthermore, since optimized codes for SCD are not optimal for SC list decoders (SCLD), we propose a rate matching algorithm to find the best rate for SCLD while using the polar codes optimized for SCD. The resulting codes provide throughput close to the capacity with low decoding complexity when used with NC or CC HARQ

    Luby Transform Coding Aided Bit-Interleaved Coded Modulation for the Wireless Internet

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    Bit-Interleaved Coded Modulation using Iterative Decoding (BICM-ID) is amalgamated with Luby Transform (LT) coding. The resultant joint design of the physical and data link layer substantially improves the attainable Bit Error Rate (BER) performance. A Cyclic Redundancy Check (CRC) combined with a novel Log-Likelihood Ratio (LLR) based packet reliability estimation method is proposed for the sake of detecting and disposing of erroneous packets. Subsequently, bit-by-bit LT decoding is proposed, which facilitates a further BER improvement at a lower number of BICM-ID iterations. Finally, we revisit the pseudo random generator function used for designing the LT generator matrix

    Relay Switching Aided Turbo Coded Hybrid-ARQ for Correlated Fading Channel

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    Hybrid-Automatic-Repeat-reQuest (HARQ) has become an indispensable technique in reliable communications systems. However, its performance is inevitably affected by the channel’s fading correlation. In this paper, we proposed a novel relay-switching aided HARQ scheme in order to mitigate the detrimental effects of correlated fading without unduly increasing the system’s complexity and delay. Our results show that the proposed relay-switching regime operates efficiently in correlated channels, hence significantly reduces the error floor of turbo-coded HARQ. Additionally, a HARQ scheme using Segment Selective Repeat (SSR) is incorporated in the relay-switching scheme for achieving further improvements. Quantitatively, the proposed relay-switching aided turbo-coded HARQ scheme using SSR may achieve an approximately 2 dB gain, compared to the conventional amplify-and-forward aided turbo coded HARQ arrangement using Chase Combining. Index Terms - Relay switching, correlated fading channel, Hybrid-ARQ, turbo codes, chase combining, incremental redundancy, selective segment repeat

    H2-ARQ-relaying: spectrum and energy efficiency perspectives

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    In this paper, we propose novel Hybrid Automatic Repeat re-Quest (HARQ) strategies used in conjunction with hybrid relaying schemes, named as H2-ARQ-Relaying. The strategies allow the relay to dynamically switch between amplify-and-forward/compress-and-forward and decode-and-forward schemes according to its decoding status. The performance analysis is conducted from both the spectrum and energy efficiency perspectives. The spectrum efficiency of the proposed strategies, in terms of the maximum throughput, is significantly improved compared with their non-hybrid counterparts under the same constraints. The consumed energy per bit is optimized by manipulating the node activation time, the transmission energy and the power allocation between the source and the relay. The circuitry energy consumption of all involved nodes is taken into consideration. Numerical results shed light on how and when the energy efficiency can be improved in cooperative HARQ. For instance, cooperative HARQ is shown to be energy efficient in long distance transmission only. Furthermore, we consider the fact that the compress-and-forward scheme requires instantaneous signal to noise ratios of all three constituent links. However, this requirement can be impractical in some cases. In this regard, we introduce an improved strategy where only partial and affordable channel state information feedback is needed

    Wireless Data Acquisition for Edge Learning: Data-Importance Aware Retransmission

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    By deploying machine-learning algorithms at the network edge, edge learning can leverage the enormous real-time data generated by billions of mobile devices to train AI models, which enable intelligent mobile applications. In this emerging research area, one key direction is to efficiently utilize radio resources for wireless data acquisition to minimize the latency of executing a learning task at an edge server. Along this direction, we consider the specific problem of retransmission decision in each communication round to ensure both reliability and quantity of those training data for accelerating model convergence. To solve the problem, a new retransmission protocol called data-importance aware automatic-repeat-request (importance ARQ) is proposed. Unlike the classic ARQ focusing merely on reliability, importance ARQ selectively retransmits a data sample based on its uncertainty which helps learning and can be measured using the model under training. Underpinning the proposed protocol is a derived elegant communication-learning relation between two corresponding metrics, i.e., signal-to-noise ratio (SNR) and data uncertainty. This relation facilitates the design of a simple threshold based policy for importance ARQ. The policy is first derived based on the classic classifier model of support vector machine (SVM), where the uncertainty of a data sample is measured by its distance to the decision boundary. The policy is then extended to the more complex model of convolutional neural networks (CNN) where data uncertainty is measured by entropy. Extensive experiments have been conducted for both the SVM and CNN using real datasets with balanced and imbalanced distributions. Experimental results demonstrate that importance ARQ effectively copes with channel fading and noise in wireless data acquisition to achieve faster model convergence than the conventional channel-aware ARQ.Comment: This is an updated version: 1) extension to general classifiers; 2) consideration of imbalanced classification in the experiments. Submitted to IEEE Journal for possible publicatio

    Cognitive Access Policies under a Primary ARQ process via Forward-Backward Interference Cancellation

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    This paper introduces a novel technique for access by a cognitive Secondary User (SU) using best-effort transmission to a spectrum with an incumbent Primary User (PU), which uses Type-I Hybrid ARQ. The technique leverages the primary ARQ protocol to perform Interference Cancellation (IC) at the SU receiver (SUrx). Two IC mechanisms that work in concert are introduced: Forward IC, where SUrx, after decoding the PU message, cancels its interference in the (possible) following PU retransmissions of the same message, to improve the SU throughput; Backward IC, where SUrx performs IC on previous SU transmissions, whose decoding failed due to severe PU interference. Secondary access policies are designed that determine the secondary access probability in each state of the network so as to maximize the average long-term SU throughput by opportunistically leveraging IC, while causing bounded average long-term PU throughput degradation and SU power expenditure. It is proved that the optimal policy prescribes that the SU prioritizes its access in the states where SUrx knows the PU message, thus enabling IC. An algorithm is provided to optimally allocate additional secondary access opportunities in the states where the PU message is unknown. Numerical results are shown to assess the throughput gain provided by the proposed techniques.Comment: 16 pages, 11 figures, 2 table

    Energy Efficiency in Communications and Networks

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    The topic of "Energy Efficiency in Communications and Networks" attracts growing attention due to economical and environmental reasons. The amount of power consumed by information and communication technologies (ICT) is rapidly increasing, as well as the energy bill of service providers. According to a number of studies, ICT alone is responsible for a percentage which varies from 2% to 10% of the world power consumption. Thus, driving rising cost and sustainability concerns about the energy footprint of the IT infrastructure. Energy-efficiency is an aspect that until recently was only considered for battery driven devices. Today we see energy-efficiency becoming a pervasive issue that will need to be considered in all technology areas from device technology to systems management. This book is seeking to provide a compilation of novel research contributions on hardware design, architectures, protocols and algorithms that will improve the energy efficiency of communication devices and networks and lead to a more energy proportional technology infrastructure
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