55,486 research outputs found
Experimental Investigation of Deep Learning for Digital Signal Processing in Short Reach Optical Fiber Communications
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
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 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
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
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
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 when 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
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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