566 research outputs found
Adaptive Bayesian decision feedback equalizer for dispersive mobile radio channels
The paper investigates adaptive equalization of time dispersive mobile ratio fading channels and develops a robust high performance Bayesian decision feedback equalizer (DFE). The characteristics and implementation aspects of this Bayesian DFE are analyzed, and its performance is compared with those of the conventional symbol or fractional spaced DFE and the maximum likelihood sequence estimator (MLSE). In terms of computational complexity, the adaptive Bayesian DFE is slightly more complex than the conventional DFE but is much simpler than the adaptive MLSE. In terms of error rate in symbol detection, the adaptive Bayesian DFE outperforms the conventional DFE dramatically. Moreover, for severely fading multipath channels, the adaptive MLSE exhibits significant degradation from the theoretical optimal performance and becomes inferior to the adaptive Bayesian DFE
Space-time processing for wireless mobile communications
Intersymbol interference (ISI) and co-channel interference (CCI) are two major
obstacles to high speed data transmission in wireless cellular communications
systems. Unlike thermal noise, their effects cannot be removed by
increasing the signal power and are time-varying due to the relative motion
between the transmitters and receivers. Space-time processing offers a signal
processing framework to optimally integrate the spatial and temporal properties
of the signal for maximal signal reception and at the same time, mitigate
the ISI and CCI impairments. In this thesis, we focus on the development of
this emerging technology to combat the undesirable effects of ISI and CCL
We first develop a convenient mathematical model to parameterize the
space-time multipath channel based on signal path power, directions and
times of arrival. Starting from the continuous time-domain, we derive compact
expressions of the vector space-time channel model that lead to the
notion of block space-time manifold, Under certain identifiability conditions,
the noiseless vector-channel outputs will lie on a subspace constructed from
a set. of basis belonging to the block space-time manifold. This is an important
observation as many high resolution array processing algorithms Can be
applied directly to estimate the multi path channel parameters.
Next we focus on the development of semi-blind channel identification
and equalization algorithms for fast time-varying multi path channels. Specifically.
we develop space-time processing algorithms for wireless TDMA networks that use short burst data formats with extremely short training data.
sequences. Due to the latter, the estimated channel parameters are extremely
unreliable for equalization with conventional adaptive methods. We approach
the channel acquisition, tracking and equalization problems jointly, and exploit
the richness of the inherent structural relationship between the channel
parameters and the data sequence by repeated use of available data through a forward- backward optimization procedure. This enables the fuller exploitation
of the available data. Our simulation studies show that significant performance
gains are achieved over conventional methods.
In the final part of this thesis, we address the problem identifying and
equalizing multi path communication channels in the presence of strong CCl.
By considering CCI as stochasic processes, we find that temporal diversity
can be gained by observing the channel outputs from a tapped delay line. Together with the assertion that the finite alphabet property of the information
sequences can offer additional information about the channel parameters and
the noise-plus-covariance matrix, we develop a spatial temporal algorithm,
iterative reweighting alternating minimization, to estimate the channel parameters
and information sequence in a weighted least squares framework.
The proposed algorithm is robust as it does not require knowledge of the
number of CCI nor their structural information. Simulation studies demonstrate
its efficacy over many reported methods
Adaptive equalisation for fading digital communication channels
This thesis considers the design of new adaptive equalisers for fading digital communication channels. The role of equalisation is discussed in the context of the functions of a digital radio communication system and both conventional and more recent novel equaliser designs are described. The application of recurrent neural networks to the problem of equalisation is developed from a theoretical study of a single node structure to the design of multinode structures. These neural networks are shown to cancel intersymbol interference in a manner mimicking conventional techniques and simulations demonstrate their sensitivity to symbol estimation errors. In addition the error mechanisms of conventional maximum likelihood equalisers operating on rapidly time-varying channels are investigated and highlight the problems of channel estimation using delayed and often incorrect symbol estimates. The relative sensitivity of Bayesian equalisation techniques to errors in the channel estimate is studied and demonstrates that the structure's equalisation capability is also susceptible to such errors. Applications of multiple channel estimator methods are developed, leading to reduced complexity structures which trade performance for a smaller computational load. These novel structures are shown to provide an improvement over the conventional techniques, especially for rapidly time-varying channels, by reducing the time delay in the channel estimation process. Finally, the use of confidence measures of the equaliser's symbol estimates in order to improve channel estimation is studied and isolates the critical areas in the development of the technique â the production of reliable confidence measures by the equalisers and the statistics of symbol estimation error bursts
Techniques of detection, estimation and coding for fading channels
The thesis describes techniques of detection, coding and estimation, for use in
high speed serial modems operating over fading channels such as HF radio and land mobile
radio links. The performance of the various systems that employ the above techniques are
obtained via computer simulation tests.
A review of the characteristics of HF radio channels is first presented, leading
to the development of an appropriate channel model which imposes Rayleigh fading on the
transmitted signal. Detection processes for a 4.8 kbit/s HF radio modem are then
discussed, the emphasis, here, being on variants of the maximum likelihood detector that is
implemented by the Viterbi algorithm. The performance of these detectors are compared
with that of a nonlinear equalizer operating under the same conditions, and the detector
which offers the best compromise between performance and complexity is chosen for
further tests.
Forward error correction, in the form of trellis coded modulation, is next
introduced. An appropriate 8-PSK coded modulation scheme is discussed, and its
operation over the above mentioned HF radio modem is evaluated. Performance
comparisons are made of the coded and uncoded systems.
Channel estimation techniques for fast fading channels akin to cellular land
mobile radio links, are next discussed. A suitable model for a fast fading channel is
developed, and some novel estimators are tested over this channel. Computer simulation
tests are also used to study the feasibility of the simultaneous transmission of two 4-level
QAM signals occupying the same frequency band, when each of these signals are
transmitted at 24 kbit/s over two independently fading channels, to a single receiver. A
novel combined detector/estimator is developed for this purpose.
Finally, the performance of the complete 4.8 kbit/s HF radio modem is
obtained, when all the functions of detection, estimation and prefiltering are present, where
the prefilter and associated processor use a recently developed technique for the adjustment
of its tap gains and for the estimation of the minimum phase sampled impulse response
Adaptive estimation and equalisation of the high frequency communications channel
SIGLEAvailable from British Library Document Supply Centre- DSC:D94945 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
Performance of adaptive bayesian equalizers in outdoor environments
Outdoor communications are affected by multipath propagation that imposes an upper limit on the system data rate and restricts possible applications. In order to overcome the degrading effect introduced by the channel, conventional equalizers implemented with digital filters have been traditionally used. A new approach based on neural networks is considered. In particular, the behavior of the adaptive Bayesian equalizer implemented by means of radial basis functions applied to the channel equalization of radio outdoor environments has been analyzed. The method used to train the equalizer coefficients is based on a channel response estimation. We compare the results obtained with three channel estimation methods: the least sum of square errors (LSSE) channel estimation algorithm, recursive least square (RLS) algorithm employed only to obtain one channel estimation and, finally, the RLS algorithm used to estimate the channel every decided symbol for the whole frame.Peer ReviewedPostprint (published version
An adaptive channel estimator for CDMA systems in multipath fading channels
Journal ArticleABSTRACT CDMA systems in multipath fading channels need to estimate channel parameters for coherent detection of the transmitted signals. In this paper we present a simple but effective channel estimation algorithm that can be incorporated into most types of multiuser receivers to obtain good detection performance. This technique uses a set of correlation filters to independently estimate each of the channel parameters. One advantage our method has over subspace-based algorithms for channel estimation is that it can estimate the channel parameters without phase or amplitude ambiguity. Simulation results demonstrating that our channel estimator is capable of tracking reasonably fast fading channels are also presented in the paper
Iterative receivers and multichannel equalisation for time division multiple access systems
The thesis introduces receiver algorithms improving the performance of TDMA mobile radio systems. Particularly, we consider receivers utilising side information, which can be obtained from the error control coding or by having a priori knowledge of interference sources. Iterative methods can be applied in the former case and interference suppression techniques in the latter.
Convolutional coding adds redundant information into the signal and thereby protects messages transmitted over a radio channel. In the coded systems the receiver is usually comprised of separate channel estimation, detection and channel decoding tasks due to complexity restrictions. This suboptimal solution suffers from performance degradation compared to the optimal solution achieved by optimising the joint probability of information bits, transmitted symbols and channel impulse response. Conventional receiver utilises estimated channel state information in the detection and detected symbols in the channel decoding to finally obtain information bits. However, the channel decoder provides also extrinsic information on the bit probabilities, which is independent of the received information at the equaliser input. Therefore it is beneficial to re-perform channel estimation and detection using this new extrinsic information together with the original input signal.
We apply iterative receiver techniques mainly to Enhanced General Packet Radio System (EGPRS) using GMSK modulation for iterative channel estimation and 8-PSK modulation for iterative detection scheme. Typical gain for iterative detection is around 2Â dB and for iterative channel estimation around 1Â dB. Furthermore, we suggest two iteration rounds as a reasonable complexity/performance trade-off. To obtain further complexity reduction we introduce the soft trellis decoding technique that reduces the decoder complexity significantly in the iterative schemes.
Cochannel interference (CCI) originates from the nearby cells that are reusing the same transmission frequency. In this thesis we consider CCI suppression by joint detection (JD) technique, which detects simultaneously desired and interfering signals. Because of the complexity limitations we only consider JD for two binary modulated signals. Therefore it is important to find the dominant interfering signal (DI) to achieve the best performance. In the presence of one strong DI, the JD provides major improvement in the receiver performance.
The JD requires joint channel estimation (JCE) for the two signals. However, the JCE makes the implementation of the JD more difficult, since it requires synchronised network and unique training sequences with low cross-correlation for the two signals.reviewe
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