35,989 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
A Linear Multi-User Detector for STBC MC-CDMA Systems based on the Adaptive Implementation of the Minimum-Conditional Bit-Error-Rate Criterion and on Genetic Algorithm-assisted MMSE Channel Estimation
The implementation of efficient baseband receivers characterized by affordable computational load is a crucial point in the development of transmission systems exploiting diversity in different domains. In this paper, we are proposing a linear multi-user detector for MIMO MC-CDMA systems with Alamouti’s Space-Time Block Coding, inspired by the concept of Minimum Conditional Bit-Error-Rate (MCBER) and relying on Genetic-Algorithm (GA)-assisted MMSE channel estimation. The MCBER combiner has been implemented in adaptive way by using Least-Mean-Square (LMS) optimization. Firstly, we shall analyze the proposed adaptive MCBER MUD receiver with ideal knowledge of Channel Status Information (CSI). Afterwards, we shall consider the complete receiver structure, encompassing also the non-ideal GA-assisted channel estimation. Simulation results evidenced that the proposed MCBER receiver always outperforms state-of-the-art receiver schemes based on EGC and MMSE criterion exploiting the same degree of channel knowledge (i.e. ideal or estimated CSI)
Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for MIMO Systems
In this work, decision feedback (DF) detection algorithms based on multiple
processing branches for multi-input multi-output (MIMO) spatial multiplexing
systems are proposed. The proposed detector employs multiple cancellation
branches with receive filters that are obtained from a common matrix inverse
and achieves a performance close to the maximum likelihood detector (MLD).
Constrained minimum mean-squared error (MMSE) receive filters designed with
constraints on the shape and magnitude of the feedback filters for the
multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive
implementation of the proposed MB-MMSE-DF detector is developed along with a
recursive least squares-type algorithm for estimating the parameters of the
receive filters when the channel is time-varying. A soft-output version of the
MB-MMSE-DF detector is also proposed as a component of an iterative detection
and decoding receiver structure. A computational complexity analysis shows that
the MB-MMSE-DF detector does not require a significant additional complexity
over the conventional MMSE-DF detector, whereas a diversity analysis discusses
the diversity order achieved by the MB-MMSE-DF detector. Simulation results
show that the MB-MMSE-DF detector achieves a performance superior to existing
suboptimal detectors and close to the MLD, while requiring significantly lower
complexity.Comment: 10 figures, 3 tables; IEEE Transactions on Wireless Communications,
201
Non-linear echo cancellation - a Bayesian approach
Echo cancellation literature is reviewed, then a Bayesian model is introduced and it is shown how how it can be used to model and fit nonlinear channels. An algorithm for cancellation of echo over a nonlinear channel is developed and tested. It is shown that this nonlinear algorithm converges for both linear and nonlinear channels and is superior to linear echo cancellation for canceling an echo through a nonlinear echo-path channel
Adaptive Subcarrier PSK Intensity Modulation in Free Space Optical Systems
We propose an adaptive transmission technique for free space optical (FSO)
systems, operating in atmospheric turbulence and employing subcarrier phase
shift keying (S-PSK) intensity modulation. Exploiting the constant envelope
characteristics of S-PSK, the proposed technique offers efficient utilization
of the FSO channel capacity by adapting the modulation order of S-PSK,
according to the instantaneous state of turbulence induced fading and a
pre-defined bit error rate (BER) requirement. Novel expressions for the
spectral efficiency and average BER of the proposed adaptive FSO system are
presented and performance investigations under various turbulence conditions
and target BER requirements are carried out. Numerical results indicate that
significant spectral efficiency gains are offered without increasing the
transmitted average optical power or sacrificing BER requirements, in
moderate-to-strong turbulence conditions. Furthermore, the proposed variable
rate transmission technique is applied to multiple input multiple output (MIMO)
FSO systems, providing additional improvement in the achieved spectral
efficiency as the number of the transmit and/or receive apertures increases.Comment: Submitted To IEEE Transactions On Communication
Channel Dynamics and SNR Tracking in Millimeter Wave Cellular Systems
The millimeter wave (mmWave) frequencies are likely to play a significant
role in fifth-generation (5G) cellular systems. A key challenge in developing
systems in these bands is the potential for rapid channel dynamics: since
mmWave signals are blocked by many materials, small changes in the position or
orientation of the handset relative to objects in the environment can cause
large swings in the channel quality. This paper addresses the issue of tracking
the signal to noise ratio (SNR), which is an essential procedure for rate
prediction, handover and radio link failure detection. A simple method for
estimating the SNR from periodic synchronization signals is considered. The
method is then evaluated using real experiments in common blockage scenarios
combined with outdoor statistical models
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