883 research outputs found
Iterative decoding for MIMO channels via modified sphere decoding
In recent years, soft iterative decoding techniques have been shown to greatly improve the bit error rate performance of various communication systems. For multiantenna systems employing space-time codes, however, it is not clear what is the best way to obtain the soft information required of the iterative scheme with low complexity. In this paper, we propose a modification of the Fincke-Pohst (sphere decoding) algorithm to estimate the maximum a posteriori probability of the received symbol sequence. The new algorithm solves a nonlinear integer least squares problem and, over a wide range of rates and signal-to-noise ratios, has polynomial-time complexity. Performance of the algorithm, combined with convolutional, turbo, and low-density parity check codes, is demonstrated on several multiantenna channels. The results for systems that employ space-time modulation schemes seem to indicate that the best performing schemes are those that support the highest mutual information between the transmitted and received signals, rather than the best diversity gain
Performance Analysis and Enhancement of Multiband OFDM for UWB Communications
In this paper, we analyze the frequency-hopping orthogonal frequency-division
multiplexing (OFDM) system known as Multiband OFDM for high-rate wireless
personal area networks (WPANs) based on ultra-wideband (UWB) transmission.
Besides considering the standard, we also propose and study system performance
enhancements through the application of Turbo and Repeat-Accumulate (RA) codes,
as well as OFDM bit-loading. Our methodology consists of (a) a study of the
channel model developed under IEEE 802.15 for UWB from a frequency-domain
perspective suited for OFDM transmission, (b) development and quantification of
appropriate information-theoretic performance measures, (c) comparison of these
measures with simulation results for the Multiband OFDM standard proposal as
well as our proposed extensions, and (d) the consideration of the influence of
practical, imperfect channel estimation on the performance. We find that the
current Multiband OFDM standard sufficiently exploits the frequency selectivity
of the UWB channel, and that the system performs in the vicinity of the channel
cutoff rate. Turbo codes and a reduced-complexity clustered bit-loading
algorithm improve the system power efficiency by over 6 dB at a data rate of
480 Mbps.Comment: 32 pages, 10 figures, 1 table. Submitted to the IEEE Transactions on
Wireless Communications (Sep. 28, 2005). Minor revisions based on reviewers'
comments (June 23, 2006
Binary Message Passing Decoding of Product-like Codes
We propose a novel binary message passing decoding algorithm for product-like
codes based on bounded distance decoding (BDD) of the component codes. The
algorithm, dubbed iterative BDD with scaled reliability (iBDD-SR), exploits the
channel reliabilities and is therefore soft in nature. However, the messages
exchanged by the component decoders are binary (hard) messages, which
significantly reduces the decoder data flow. The exchanged binary messages are
obtained by combining the channel reliability with the BDD decoder output
reliabilities, properly conveyed by a scaling factor applied to the BDD
decisions. We perform a density evolution analysis for generalized low-density
parity-check (GLDPC) code ensembles and spatially coupled GLDPC code ensembles,
from which the scaling factors of the iBDD-SR for product and staircase codes,
respectively, can be obtained. For the white additive Gaussian noise channel,
we show performance gains up to dB and dB for product and
staircase codes compared to conventional iterative BDD (iBDD) with the same
decoder data flow. Furthermore, we show that iBDD-SR approaches the performance
of ideal iBDD that prevents miscorrections.Comment: Accepted for publication in the IEEE Transactions on Communication
Cyclic-Coded Integer-Forcing Equalization
A discrete-time intersymbol interference channel with additive Gaussian noise
is considered, where only the receiver has knowledge of the channel impulse
response. An approach for combining decision-feedback equalization with channel
coding is proposed, where decoding precedes the removal of intersymbol
interference. This is accomplished by combining the recently proposed
integer-forcing equalization approach with cyclic block codes. The channel
impulse response is linearly equalized to an integer-valued response. This is
then utilized by leveraging the property that a cyclic code is closed under
(cyclic) integer-valued convolution. Explicit bounds on the performance of the
proposed scheme are also derived
Two-tier channel estimation aided near-capacity MIMO transceivers relying on norm-based joint transmit and receive antenna selection
We propose a norm-based joint transmit and receive antenna selection (NBJTRAS) aided near-capacity multiple-input multiple-output (MIMO) system relying on the assistance of a novel two-tier channel estimation scheme. Specifically, a rough estimate of the full MIMO channel is first generated using a low-complexity, low-training-overhead minimum mean square error based channel estimator, which relies on reusing a modest number of radio frequency (RF) chains. NBJTRAS is then carried out based on this initial full MIMO channel estimate. The NBJTRAS aided MIMO system is capable of significantly outperforming conventional MIMO systems equipped with the same modest number of RF chains, while dispensing with the idealised simplifying assumption of having perfectly known channel state information (CSI). Moreover, the initial subset channel estimate associated with the selected subset MIMO channel matrix is then used for activating a powerful semi-blind joint channel estimation and turbo detector-decoder, in which the channel estimate is refined by a novel block-of-bits selection based soft-decision aided channel estimator (BBSB-SDACE) embedded in the iterative detection and decoding process. The joint channel estimation and turbo detection-decoding scheme operating with the aid of the proposed BBSB-SDACE channel estimator is capable of approaching the performance of the near-capacity maximumlikelihood (ML) turbo transceiver associated with perfect CSI. This is achieved without increasing the complexity of the ML turbo detection and decoding process
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
Channel Coding at Low Capacity
Low-capacity scenarios have become increasingly important in the technology
of the Internet of Things (IoT) and the next generation of mobile networks.
Such scenarios require efficient and reliable transmission of information over
channels with an extremely small capacity. Within these constraints, the
performance of state-of-the-art coding techniques is far from optimal in terms
of either rate or complexity. Moreover, the current non-asymptotic laws of
optimal channel coding provide inaccurate predictions for coding in the
low-capacity regime. In this paper, we provide the first comprehensive study of
channel coding in the low-capacity regime. We will investigate the fundamental
non-asymptotic limits for channel coding as well as challenges that must be
overcome for efficient code design in low-capacity scenarios.Comment: 39 pages, 5 figure
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