55,486 research outputs found

    Experimental Investigation of Deep Learning for Digital Signal Processing in Short Reach Optical Fiber Communications

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    We investigate methods for experimental performance enhancement of auto-encoders based on a recurrent neural network (RNN) for communication over dispersive nonlinear channels. In particular, our focus is on the recently proposed sliding window bidirectional RNN (SBRNN) optical fiber autoencoder. We show that adjusting the processing window in the sequence estimation algorithm at the receiver improves the reach of simple systems trained on a channel model and applied "as is" to the transmission link. Moreover, the collected experimental data was used to optimize the receiver neural network parameters, allowing to transmit 42 Gb/s with bit-error rate (BER) below the 6.7% hard-decision forward error correction threshold at distances up to 70km as well as 84 Gb/s at 20 km. The investigation of digital signal processing (DSP) optimized on experimental data is extended to pulse amplitude modulation with receivers performing sliding window sequence estimation using a feed-forward or a recurrent neural network as well as classical nonlinear Volterra equalization. Our results show that, for fixed algorithm memory, the DSP based on deep learning achieves an improved BER performance, allowing to increase the reach of the system.Comment: Invited paper at the IEEE International Workshop on Signal Processing Systems (SiPS) 202

    Rate-Flexible Fast Polar Decoders

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    Polar codes have gained extensive attention during the past few years and recently they have been selected for the next generation of wireless communications standards (5G). Successive-cancellation-based (SC-based) decoders, such as SC list (SCL) and SC flip (SCF), provide a reasonable error performance for polar codes at the cost of low decoding speed. Fast SC-based decoders, such as Fast-SSC, Fast-SSCL, and Fast-SSCF, identify the special constituent codes in a polar code graph off-line, produce a list of operations, store the list in memory, and feed the list to the decoder to decode the constituent codes in order efficiently, thus increasing the decoding speed. However, the list of operations is dependent on the code rate and as the rate changes, a new list is produced, making fast SC-based decoders not rate-flexible. In this paper, we propose a completely rate-flexible fast SC-based decoder by creating the list of operations directly in hardware, with low implementation complexity. We further propose a hardware architecture implementing the proposed method and show that the area occupation of the rate-flexible fast SC-based decoder in this paper is only 38%38\% of the total area of the memory-based base-line decoder when 5G code rates are supported

    Burst-by-Burst Adaptive Decision Feedback Equalised TCM, TTCM and BICM for H.263-Assisted Wireless Video Telephony

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    Decision Feedback Equaliser (DFE) aided wideband Burst-by-Burst (BbB) Adaptive Trellis Coded Modulation (TCM), Turbo Trellis Coded Modulation (TTCM) and Bit-Interleaved Coded Modulation (BICM) assisted H.263-based video transceivers are proposed and characterised in performance terms when communicating over the COST 207 Typical Urban wideband fading channel. Specifically, four different modulation modes, namely 4QAM, 8PSK, 16QAM and 64QAM are invoked and protected by the above-mentioned coded modulation schemes. The TTCM assisted scheme was found to provide the best video performance, although at the cost of the highest complexity. A range of lower-complexity arrangements will also be characterised. Finally, in order to confirm these findings in an important practical environment, we have also investigated the adaptive TTCM scheme in the CDMA-based Universal Mobile Telecommunications System's (UMTS) Terrestrial Radio Access (UTRA) scenario and the good performance of adaptive TTCM scheme recorded when communicating over the COST 207 channels was retained in the UTRA environment

    Design issues toward a cost effective physical layer for multiband OFDM (ECMA-368) in consumer products

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    The creation of Wireless Personal Area Networks (WPANs) offers the Consumer Electronics industry a mechanism to truly unwire consumer products, leading to portability and ease of installation as never seen before. WPAN's can offer data-rates exceeding those that are required to convey high quality broadcast video, thus users can easily connect to high quality video for multimedia presentations in education, libraries, advertising, or have a wireless connection at home. There have been many WPAN proposals, but this paper concentrates on ECMA-368 as this standard has the largest industrial and implementers' forum backing. With the aim to effective consumer electronic define and create cost equipment this paper discusses the technology behind ECMA-368 physical layer, the design freedom availabilities, the required processing, buffer memory requirements and implementation considerations while concentrating on supporting all the offered data-rates(1)

    Low Complexity Decoding for Higher Order Punctured Trellis-Coded Modulation Over Intersymbol Interference Channels

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    Trellis-coded modulation (TCM) is a power and bandwidth efficient digital transmission scheme which offers very low structural delay of the data stream. Classical TCM uses a signal constellation of twice the cardinality compared to an uncoded transmission with one bit of redundancy per PAM symbol, i.e., application of codes with rates n1n\frac{n-1}{n} when 2n2^{n} denotes the cardinality of the signal constellation. Recently published work allows rate adjustment for TCM by means of puncturing the convolutional code (CC) on which a TCM scheme is based on. In this paper it is shown how punctured TCM-signals transmitted over intersymbol interference (ISI) channels can favorably be decoded. Significant complexity reductions at only minor performance loss can be achieved by means of reduced state sequence estimation.Comment: 4 pages, 5 figures, 3 algorithms, accepted and published at 6th International Symposium on Communications, Control, and Signal Processing (ISCCSP 2014

    Diffusive MIMO Molecular Communications: Channel Estimation, Equalization and Detection

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    In diffusion-based communication, as for molecular systems, the achievable data rate is low due to the stochastic nature of diffusion which exhibits a severe inter-symbol-interference (ISI). Multiple-Input Multiple-Output (MIMO) multiplexing improves the data rate at the expense of an inter-link interference (ILI). This paper investigates training-based channel estimation schemes for diffusive MIMO (D-MIMO) systems and corresponding equalization methods. Maximum likelihood and least-squares estimators of mean channel are derived, and the training sequence is designed to minimize the mean square error (MSE). Numerical validations in terms of MSE are compared with Cramer-Rao bound derived herein. Equalization is based on decision feedback equalizer (DFE) structure as this is effective in mitigating diffusive ISI/ILI. Zero-forcing, minimum MSE and least-squares criteria have been paired to DFE, and their performances are evaluated in terms of bit error probability. Since D-MIMO systems are severely affected by the ILI because of short transmitters inter-distance, D-MIMO time interleaving is exploited as countermeasure to mitigate the ILI with remarkable performance improvements. The feasibility of a block-type communication including training and data equalization is explored for D-MIMO, and system-level performances are numerically derived.Comment: Accepted paper at IEEE transaction on Communicatio
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