2,662 research outputs found
Optical Time-Frequency Packing: Principles, Design, Implementation, and Experimental Demonstration
Time-frequency packing (TFP) transmission provides the highest achievable
spectral efficiency with a constrained symbol alphabet and detector complexity.
In this work, the application of the TFP technique to fiber-optic systems is
investigated and experimentally demonstrated. The main theoretical aspects,
design guidelines, and implementation issues are discussed, focusing on those
aspects which are peculiar to TFP systems. In particular, adaptive compensation
of propagation impairments, matched filtering, and maximum a posteriori
probability detection are obtained by a combination of a butterfly equalizer
and four 8-state parallel Bahl-Cocke-Jelinek-Raviv (BCJR) detectors. A novel
algorithm that ensures adaptive equalization, channel estimation, and a proper
distribution of tasks between the equalizer and BCJR detectors is proposed. A
set of irregular low-density parity-check codes with different rates is
designed to operate at low error rates and approach the spectral efficiency
limit achievable by TFP at different signal-to-noise ratios. An experimental
demonstration of the designed system is finally provided with five
dual-polarization QPSK-modulated optical carriers, densely packed in a 100 GHz
bandwidth, employing a recirculating loop to test the performance of the system
at different transmission distances.Comment: This paper has been accepted for publication in the IEEE/OSA Journal
of Lightwave Technolog
Constellation Shaping for WDM systems using 256QAM/1024QAM with Probabilistic Optimization
In this paper, probabilistic shaping is numerically and experimentally
investigated for increasing the transmission reach of wavelength division
multiplexed (WDM) optical communication system employing quadrature amplitude
modulation (QAM). An optimized probability mass function (PMF) of the QAM
symbols is first found from a modified Blahut-Arimoto algorithm for the optical
channel. A turbo coded bit interleaved coded modulation system is then applied,
which relies on many-to-one labeling to achieve the desired PMF, thereby
achieving shaping gain. Pilot symbols at rate at most 2% are used for
synchronization and equalization, making it possible to receive input
constellations as large as 1024QAM. The system is evaluated experimentally on a
10 GBaud, 5 channels WDM setup. The maximum system reach is increased w.r.t.
standard 1024QAM by 20% at input data rate of 4.65 bits/symbol and up to 75% at
5.46 bits/symbol. It is shown that rate adaptation does not require changing of
the modulation format. The performance of the proposed 1024QAM shaped system is
validated on all 5 channels of the WDM signal for selected distances and rates.
Finally, it was shown via EXIT charts and BER analysis that iterative
demapping, while generally beneficial to the system, is not a requirement for
achieving the shaping gain.Comment: 10 pages, 12 figures, Journal of Lightwave Technology, 201
Synchronization for capacity -approaching coded communication systems
The dissertation concentrates on synchronization of capacity approaching error-correction codes that are deployed in noisy channels with very low signal-to-noise ratio (SNR). The major topics are symbol timing synchronization and frame synchronization.;Capacity-approaching error-correction codes, like turbo codes and low-density parity-check (LDPC) codes, are capable of reaching very low bit error rates and frame error rates in noisy channels by iterative decoding. To fully achieve the potential decoding capability of Turbo codes and LDPC codes, proper symbol timing synchronization, frame synchronization and channel state estimation are required. The dissertation proposes a joint estimator of symbol time delay and channel SNR for symbol timing recovery, and a maximum a posteriori (MAP) frame synchronizer for frame synchronization.;Symbol timing recovery is implemented by sampling and interpolation. The received signal is sampled multiple times per symbol period with unknown delay and unknown SNR. A joint estimator estimates the time delay and the SNR. The signal is rebuilt by interpolating available samples using estimated time delay. The intermediate decoding results enable decision-feedback estimation. The estimates of time delay and SNR are refined by iterative processing. This refinement improves the system performance significantly.;Usually the sampling rate is assumed to be a strict integer multiple of the symbol rate. However, in a practical system the local oscillators in the transmitter and the receiver may have random drifts. Therefore the sampling rate is no longer an exact multiple of the symbol rate, and the sampling time follows a random walk. This random walk may harm the system performance severely. The dissertation analyzes the effect of random time walks and proposes to mitigate the effect by overlapped sliding windows and iterative processing.;Frame synchronization is required to find the correct boundaries of codewords. MAP frame synchronization in the sense of minimizing the frame sync failure rate is investigated. The MAP frame synchronizer explores low-density parity-check attributes of the capacity-approaching codes. The accuracy of frame synchronization is adequate for considered coded systems to work reliably under very low SNR
A Belief Propagation Based Framework for Soft Multiple-Symbol Differential Detection
Soft noncoherent detection, which relies on calculating the \textit{a
posteriori} probabilities (APPs) of the bits transmitted with no channel
estimation, is imperative for achieving excellent detection performance in
high-dimensional wireless communications. In this paper, a high-performance
belief propagation (BP)-based soft multiple-symbol differential detection
(MSDD) framework, dubbed BP-MSDD, is proposed with its illustrative application
in differential space-time block-code (DSTBC)-aided ultra-wideband impulse
radio (UWB-IR) systems. Firstly, we revisit the signal sampling with the aid of
a trellis structure and decompose the trellis into multiple subtrellises.
Furthermore, we derive an APP calculation algorithm, in which the
forward-and-backward message passing mechanism of BP operates on the
subtrellises. The proposed BP-MSDD is capable of significantly outperforming
the conventional hard-decision MSDDs. However, the computational complexity of
the BP-MSDD increases exponentially with the number of MSDD trellis states. To
circumvent this excessive complexity for practical implementations, we
reformulate the BP-MSDD, and additionally propose a Viterbi algorithm
(VA)-based hard-decision MSDD (VA-HMSDD) and a VA-based soft-decision MSDD
(VA-SMSDD). Moreover, both the proposed BP-MSDD and VA-SMSDD can be exploited
in conjunction with soft channel decoding to obtain powerful iterative
detection and decoding based receivers. Simulation results demonstrate the
effectiveness of the proposed algorithms in DSTBC-aided UWB-IR systems.Comment: 14 pages, 12 figures, 3 tables, accepted to appear on IEEE
Transactions on Wireless Communications, Aug. 201
Doctor of Philosophy
dissertationThe continuous growth of wireless communication use has largely exhausted the limited spectrum available. Methods to improve spectral efficiency are in high demand and will continue to be for the foreseeable future. Several technologies have the potential to make large improvements to spectral efficiency and the total capacity of networks including massive multiple-input multiple-output (MIMO), cognitive radio, and spatial-multiplexing MIMO. Of these, spatial-multiplexing MIMO has the largest near-term potential as it has already been adopted in the WiFi, WiMAX, and LTE standards. Although transmitting independent MIMO streams is cheap and easy, with a mere linear increase in cost with streams, receiving MIMO is difficult since the optimal methods have exponentially increasing cost and power consumption. Suboptimal MIMO detectors such as K-Best have a drastically reduced complexity compared to optimal methods but still have an undesirable exponentially increasing cost with data-rate. The Markov Chain Monte Carlo (MCMC) detector has been proposed as a near-optimal method with polynomial cost, but it has a history of unusual performance issues which have hindered its adoption. In this dissertation, we introduce a revised derivation of the bitwise MCMC MIMO detector. The new approach resolves the previously reported high SNR stalling problem of MCMC without the need for hybridization with another detector method or adding heuristic temperature scaling terms. Another common problem with MCMC algorithms is an unknown convergence time making predictable fixed-length implementations problematic. When an insufficient number of iterations is used on a slowly converging example, the output LLRs can be unstable and overconfident, therefore, we develop a method to identify rare, slowly converging runs and mitigate their degrading effects on the soft-output information. This improves forward-error-correcting code performance and removes a symptomatic error floor in bit-error-rates. Next, pseudo-convergence is identified with a novel way to visualize the internal behavior of the Gibbs sampler. An effective and efficient pseudo-convergence detection and escape strategy is suggested. Finally, the new excited MCMC (X-MCMC) detector is shown to have near maximum-a-posteriori (MAP) performance even with challenging, realistic, highly-correlated channels at the maximum MIMO sizes and modulation rates supported by the 802.11ac WiFi specification, 8x8 256 QAM. Further, the new excited MCMC (X-MCMC) detector is demonstrated on an 8-antenna MIMO testbed with the 802.11ac WiFi protocol, confirming its high performance. Finally, a VLSI implementation of the X-MCMC detector is presented which retains the near-optimal performance of the floating-point algorithm while having one of the lowest complexities found in the near-optimal MIMO detector literature
Nonlinear Probabilistic Constellation Shaping with Sequence Selection
Probabilistic shaping is a pragmatic approach to improve the performance of
coherent optical fiber communication systems. In the nonlinear regime, the
advantages offered by probabilistic shaping might increase thanks to the
opportunity to obtain an additional nonlinear shaping gain. Unfortunately, the
optimization of conventional shaping techniques, such as probabilistic
amplitude shaping (PAS), yields a relevant nonlinear shaping gain only in
scenarios of limited practical interest. In this manuscript we use sequence
selection to investigate the potential, opportunities, and challenges offered
by nonlinear probabilistic shaping. First, we show that ideal sequence
selection is able to provide up to 0.13 bit/s/Hz gain with respect to PAS with
an optimized blocklength. However, this additional gain is obtained only if the
selection metric accounts for the signs of the symbols: they must be known to
compute the selection metric, but there is no need to shape them. Furthermore,
we show that the selection depends in a non-critical way on the symbol rate and
link length: the sequences selected for a certain scenario still provide a
relevant gain if these are modified. Then, we analyze and compare several
practical implementations of sequence selection by taking into account
interaction with forward error correction (FEC) and complexity. Overall, the
single block and the multi block FEC-independent bit scrambling are the best
options, with a gain up to 0.08 bit/s/Hz. The main challenge and limitation to
their practical implementation remains the evaluation of the metric, whose
complexity is currently too high. Finally, we show that the nonlinear shaping
gain provided by sequence selection persists when carrier phase recovery is
included.Comment: The manuscript has been submitted for publication to the Journal of
Lightwave Technolog
Phase Noise Compensation for Nonlinearity-Tolerant Digital Subcarrier Systems With High-Order QAM
The fundamental penalty of subcarrier modulation (SCM) with independent subcarrier phase noise processing is estimated. It is shown that the fundamental signal-to-noise ratio (SNR) penalty related to poorer phase noise tolerance of decreased baudrate subcarriers increases significantly with modulation format size and can potentially exceed the gains of the nonlinear tolerance of SCM. A low-complexity algorithm is proposed for joint subcarrier phase noise processing, which is scalable in the number of subcarriers and recovers almost entirely the fundamental SNR penalty with respect to single-carrier systems operating at the same net data-rate. The proposed algorithm enables high-order modulation formats with high count of subcarriers to be safely employed for nonlinearity mitigation in optical communication systems
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