Pulse or digital communications – Equalizers – Automatic
Reexamination Certificate
1998-08-28
2001-12-04
Ghebretinsae, Temesghen (Department: 2631)
Pulse or digital communications
Equalizers
Automatic
C708S323000, C333S018000
Reexamination Certificate
active
06327302
ABSTRACT:
BACKGROUND OF THE INVENTION
Modern telecommunication has experienced explosive growth in the past decade. Distinguishing from the conventional telecommunication systems, there are two important aspects in modern telecommunication technologies, one being digital, and another being wireless. Wireless communication revolutionarily changes the way of communication and provides possibility of communication to anyone, from anywhere, at anytime. While wireless communication technology significantly changes the way people live and work, it adds tremendous challenges to communication engineering design. It is obvious that when a radio signal is transmitted through the air, the signal quality will largely depend on many variables in communication environments that are beyond our control. For example, the radio signal could be absorbed by or reflected from the buildings, mountains, or other obstacles between two points of communication. In addition, the received signal quality depends on the speed of mobile transmitter and receiver terminals. All of these increase the difficulties of maintaining a quality communication link. Furthermore, unlike a wired communication system, a wireless communication system often has problems with flat or frequency selective fading, and time dispersion.
In order to maintain a quality wireless communication signal, the radio channel must be estimated and properly compensated, and one effective means of such channel estimation and compensation is called channel equalization. Due to the time-varying nature of a radio channel, channel equalization is often designed to be adaptive, or time-varying, in order to track dynamic channel variation.
PRIOR ART
Various equalization techniques have been taught in prior arts for channel estimation and compensation and acoustic echo cancellation applications. Depending upon the application and the system requirements, an adaptive equalizer can be quite straightforward or rather complex in realization. A relatively simple equalization technique is perhaps a linear adaptive equalizer using the least mean square (LMS) algorithm. An LMS adaptive equalization minimizes an error signal, typically the mean square error between the output of an adaptive filter and the desired channel response through an adaptive process. A gradient descent adaptive algorithm is often utilized to minimize the mean square error. In a gradient descent adaptive algorithm, the gradient of the error signal with respect to filter coefficients is estimated and the filter coefficients are updated along the negative gradient direction at each iteration of the adaptive process until the mean square error is minimized. Because of its simplicity and easy implementation, LMS adaptive equalization, either linear or decision feedback, has been widely used in various applications.
Another equalization technique can be categorized as probabilistic detection algorithms. The most commonly used techniques within this category include Maximum A Posteriori probability (MAP) and Maximum Likelihood Sequence Estimation (MLSE). These techniques minimize the probability of a signal detection error and therefore require knowledge of channel characteristics and the stochastic property of channel noise. While the MAP technique detects a received signal in a symbol-by-symbol manner, the MLSE algorithm utilizes the Viterbi algorithm to minimize the probability of a sequence error. A more detailed description of equalization techniques based on probabilistic detection algorithms can be found in references such as Digital Communication (2
nd
ed. 1994) by E. A. Lee and D. G. Messerschmitt, Telecommunications Applications with TMS320C5x DSPs (Texas Instruments Application Book, 1994), and Adaptive Equalization for TDMA Digital Mobile Radio (IEEE Trans. On Vehicular Technology, Vol. 40, No. 2, May 1991) by J. G. Proakis.
The channel equalization techniques described above have both advantages and shortcomings. A simple linear adaptive equalizer is straightforward and simple to implement. However, it is less effective in severe wireless communication environments. Its limitation for wireless communication lies in the fact that the LMS algorithm is inherently a slow convergence algorithm, especially when the reference signal is highly correlated. Therefore, while the conventional LMS based equalization technique is attractive due to its simple implementation, its slow convergence property makes it difficult to track the rapid change of a radio channel due to the terminal speed and the dynamic operating environment.
In contrast to an LMS algorithm, a MAP or MLSE based equalization technique is quite effective in estimating and reducing inter-symbol interference (ISI). However, the complexity of implementing the MAP or MLSE algorithms is significantly higher than a LMS algorithm. In fact, the implementation complexity of the MAP and MLSE techniques prohibit its utility in certain applications. For example, in applications such as Personal Wireless Telecommunication (PWT) or Digital Enhanced Cordless Telecommunication (DECT), where time dispersion is typically not as severe as in cellular applications, a less complex equalization technique is often desirable because it has a lower cost.
SUMMARY OF THE INVENTION
The present invention relates to an adaptive equalizer design in a wireless communication system. More specifically, this invention describes a novel adaptive equalization method and apparatus that utilizes a fast adaptive algorithm. While the present invention is well suited for applications such as Personal Wireless Telecommunication, Digital Enhanced Cordless Telecommunication, Wireless Local Loop communication, and other cellular communication systems, it will be understood by one skilled in the art that the advantages of this invention will apply to other types of communication systems as well.
In light of the above mentioned problems associated with both least mean square algorithm and probabilistic detection algorithm equalization techniques in the prior art, it is an object of the present invention to provide an adaptive equalizer with less complexity than the commonly used MLS equalizer or MAP algorithm and a fast convergence property.
Another object of the present invention is to provide a fast adaptive algorithm that can be applied to both a linear equalizer and a decision feedback equalizer design.
A further object of the present invention is to provide a fast adaptive algorithm with a level of complexity and a structural simplicity that is close to the conventional Least Mean Square algorithm in order to also provide a channel equalization technique that has both a desirable level of accuracy and a low implementation cost.
Still another object of the invention is to utilize time-varying convergence parameters in the adaptive algorithm in order to achieve a fast convergence and to minimize the error signal.
These and other objects, features, and advantages of the present invention will be apparent from the accompanying drawings and from the detailed description that follows.
REFERENCES:
patent: 5119401 (1992-06-01), Tsujimoto
patent: 5283811 (1994-02-01), Chennakeshu et al.
patent: 5517527 (1996-05-01), Yu
patent: 5524125 (1996-06-01), Tsujimoto
patent: 5546430 (1996-08-01), Liao et al.
patent: 5581585 (1996-12-01), Takatori et al.
patent: 5777692 (1998-07-01), Ghosh
patent: 6011813 (2000-01-01), Ghosh
E.A. Lee and D.G. Messerschmitt, Digital Communication, 2ndEdition, Kluwer Academic Publishers, 1994.
Application Book, Telecommunications Applications with TMS320C5x, DSPs, Texas Instruments, 1994.
J.G. Proakis, “Adaptive Equalization for TDMA Digital Mobile Radio,” IEEE Trans. On Vehicular Technology, vol. 40, No. 2, May 1991.
P. Jung and P.W. Baiser, “VLSI Implementation of Soft Output Viterbi Equalizers for Mobile Radio Applications,” Proc. Of Vehicular Technology Society 42ndVTS Conference, pp. 577-585, 1992.
W.B. Mikhael et al, “Adaptive Filters with Individual Adaptation of Parameters,” IEEE Trans. On Circuits and Systems, vol. CAS-33, No. 7, pp. 677-685, Jul. 1
Ericsson Inc.
Ericsson Inc.
Ghebretinsae Temesghen
LandOfFree
Fast adaptive equalizer for wireless communication systems does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Fast adaptive equalizer for wireless communication systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Fast adaptive equalizer for wireless communication systems will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2574411