66 research outputs found
A low-complexity eigenfilter design method for channel shortening equalizers for DMT systems
We present a new low-complexity method for the design of channel shortening equalizers for discrete multitone (DMT) modulation systems using the eigenfilter approach. In contrast to other such methods which require a Cholesky decomposition for each delay parameter value used, ours requires only one such decomposition. Simulation results show that our method performs nearly optimally in terms of observed bit rate
Bit-Error-Rate-Minimizing Channel Shortening Using Post-FEQ Diversity Combining and a Genetic Algorithm
In advanced wireline or wireless communication systems, i.e., DSL, IEEE 802.11a/g, HIPERLAN/2, etc., a cyclic prefix which is proportional to the channel impulse response is needed to append a multicarrier modulation (MCM) frame for operating the MCM accurately. This prefix is used to combat inter symbol interference (ISI). In some cases, the channel impulse response can be longer than the cyclic prefix (CP). One of the most useful techniques to mitigate this problem is reuse of a Channel Shortening Equalizer (CSE) as a linear preprocessor before the MCM receiver in order to shorten the effective channel length. Channel shortening filter design is a widely examined topic in the literature. Most channel shortening equalizer proposals depend on perfect channel state information (CSI). However, this information may not be available in all situations. In cases where channel state information is not needed, blind adaptive equalization techniques are appropriate. In wireline communication systems (such as DMT), the CSE design is based on maximizing the bit rate, but in wireless systems (OFDM), there is a fixed bit loading algorithm, and the performance metric is Bit Error Rate (BER) minimization. In this work, a CSE is developed for multicarrier and single-carrier cyclic prefixed (SCCP) systems which attempts to minimize the BER. To minimize the BER, a Genetic Algorithm (GA), which is an optimization method based on the principles of natural selection and genetics, is used. If the CSI is shorter than the CP, the equalization can be done by a frequency domain equalizer (FEQ), which is a bank of complex scalars. However, in the literature the adaptive FEQ design has not been well examined. The second phase of this thesis focuses on different types of algorithms for adapting the FEQ and modifying the FEQ architecture to obtain a lower BER. Simulation results show that this modified architecture yields a 20 dB improvement in BER
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Channel equalization to achieve high bit rates in discrete multitone systems
textMulticarrier modulation (MCM) techniques such as orthogonal frequency division
multiplexing (OFDM) and discrete multi-tone (DMT) modulation are attractive
for high-speed data communications due to the ease with which MCM can combat
channel dispersion. With all the benefits MCM could give, DMT modulation has an
extra ability to perform dynamic bit loading, which has the potential to exploit fully
the available bandwidth in a slowly time-varying channel. In broadband wireline
communications, DMT modulation is standardized for asymmetric digital subscribe
line (ADSL) and very-high-bit-rate digital subscriber line (VDSL) modems. ADSL
and VDSL standards are used by telephone companies to provide high speed data
service to residences and offices.
In an ADSL receiver, an equalizer is required to compensate for the channel’s
dispersion in the time domain and the channel’s distortion in the frequency domain
of the transmitted waveform. This dissertation proposes design methods for linear
equalizers to increase the bit rate of the connection. The methods are amenable
to implementation on programmable fixed-point digital signal processors, which are
employed in ADSL/VDSL transceivers.
A conventional ADSL equalizer consists of a time-domain equalizer, a fast
Fourier transform, and a frequency domain equalizer. The time domain equalizer
(TEQ) is a finite impulse response filter that when coupled with a discretized channel
produces an equivalent channel whose impulse response is shorter than that of
the discretized channel. This channel shortening is required by the ADSL standards.
In this dissertation, I first propose a linear phase TEQ design that exploits symmetry
in existing eigen-filter approaches such as minimum mean square error(MMSE),
maximum shortening signal to noise ratio (MSSNR) and minimum intersymbol interference
(Min-ISI) equalizers. TEQs with symmetric coefficients can reach the
same performance as non-symmetric ones with much lower training complexity.
Second, I improve Min-ISI design. I reformulate the cost function to make
long TEQs design feasible. I remove the dependency of transmission delay in order
to reduce the complexity associated with delay optimization. The quantized
weighting is introduced to further lower the complexity. I also propose an iterative
optimization procedure of Min-ISI that completely avoids Cholesky decomposition
hence is better suited for a fixed-point implementation.
Finally I propose a dual-path TEQ structure, which designs a standard singleFIR
TEQ to achieve good bit rate over the entire transmission bandwidth, and
designs another FIR TEQ to improve the bit rate over a subset of subcarriers. Dualpath
TEQ can be viewed as a special case of a complex valued filter bank structure
that delivers the best bit rate of existing DMT equalizers. However, dual-path
TEQ provides a very good tradeoff between achievable bit rate vs. implementation
complexity on a programmable digital signal processor.Electrical and Computer Engineerin
Intersymbol and Intercarrier Interference in OFDM Transmissions through Highly Dispersive Channels
This work quantifies, for the first time, intersymbol and intercarrier
interferences induced by very dispersive channels in OFDM systems. The
resulting achievable data rate for \wam{suboptimal} OFDM transmissions is
derived based on the computation of signal-to-interference-plus-noise ratio for
arbitrary length finite duration channel impulse responses. Simulation results
point to significant differences between data rates obtained via conventional
formulations, for which interferences are supposed to be limited to two or
three blocks, versus the data rates considering the actual channel dispersion
A blind channel shortening for multiuser, multicarrier CDMA system over multipath fading channel
In this paper we derive the Multicarrier Equalization by Restoration of Redundancy (MERRY) algorithm: A blind, adaptive channel shortening algorithm for updating a Time-domain Equalizer (TEQ) in a system employing MultiCarrier Code Division Multiple Access (MC-CDMA) modulation. We show that the MERRY algorithm applied to the MC-CDMA system converges considerably more rapidly than in the Orthogonal Frequency Division Multiplexing (OFDM) system [1]. Simulations results are provided to demonstrate the performance of the algorithm
On the eigenfilter design method and its applications: a tutorial
The eigenfilter method for digital filter design involves the computation of filter coefficients as the eigenvector of an appropriate Hermitian matrix. Because of its low complexity as compared to other methods as well as its ability to incorporate various time and frequency-domain constraints easily, the eigenfilter method has been found to be very useful. In this paper, we present a review of the eigenfilter design method for a wide variety of filters, including linear-phase finite impulse response (FIR) filters, nonlinear-phase FIR filters, all-pass infinite impulse response (IIR) filters, arbitrary response IIR filters, and multidimensional filters. Also, we focus on applications of the eigenfilter method in multistage filter design, spectral/spacial beamforming, and in the design of channel-shortening equalizers for communications applications
Blind adaptive channel shortening with a generalized lag-hopping algorithm which employs squared auto-correlation minimization [GLHSAM].
A generalized blind lag-hopping adaptive channel shortening
(GLHSAM) algorithm based upon squared auto-correlation
minimization is proposed. This algorithm provides the ability
to select a level of complexity at each iteration between
the sum-squared autocorrelation minimization (SAM) algorithm
due to Martin and Johnson and the single lag autocorrelation
minimization (SLAM) algorithm proposed by Nawaz
and Chambers whilst guaranteeing convergence to high signal
to interference ratio (SIR). At each iteration a number of
unique lags are chosen randomly from the available range so
that on the average GLHSAM has the same cost as the SAM
algorithm. The performance of the proposed GLHSAM algorithm
is confirmed through simulation studies
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