Pulse or digital communications – Receivers – Interference or noise reduction
Reexamination Certificate
1999-06-03
2002-09-03
Pham, Chi (Department: 2631)
Pulse or digital communications
Receivers
Interference or noise reduction
C375S348000, C375S349000, C375S341000, C375S262000, C375S267000, C455S504000, C455S517000, C455S063300
Reexamination Certificate
active
06445757
ABSTRACT:
The invention relates to a diversity combining method in a digital radio system receiver, in which receiver matched filtering and maximum likelihood detection are used and an estimated channel impulse response and autocorrelation taps of the impulse response are generated, and in which radio system substantially all signal processing occurs as symbols and a desired signal comprises a predetermined sequence.
The invention also relates to a receiver in a digital radio system, the receiver comprising a matched filter, diversity branches and a maximum likelihood detector, the receiver being arranged to generate an estimated channel impulse response and autocorrelation taps of the impulse response, and in which radio system a desired signal comprises a predetermined sequence and in which radio system signal processing is arranged to occur as symbols.
In a radio system the quality of the connection between a base station and a subscriber terminal varies continuously. This variation is due to interfering factors on the radio path and to attenuation of the radio waves as a function of distance and time in a fading channel. Connection quality can be measured for example by observing the received power. Variance in connection quality can partly be compensated by power regulation.
However, in a digital radio system a more precise method than power measuring is needed for estimating connection quality. Then the known quality parameters are for example the bit error rate (BER) and the signal-to-noise ratio.
It is previously known to utilize decisions of the ML (Maximum Likelihood) type detection for estimating the signal-to-noise ratio of a received signal. Thus a Viterbi detector usually functions as the ML detector and a base station or subscriber terminal can be the receiver. In known solutions the Viterbi detection is performed on the received burst in full before determining the signal-to-noise ratio. However, as a Viterbi algorithm is often a too demanding measure for a digital signal processing program to perform during the processing time allowed by the receiver, separate Viterbi hardware has to be used. This has been described in greater detail in J. Hagenauer, P. Hoeher: A Viterbi Algorithm with Soft-decision Outputs and its Applications, IEEE GLOBECOM 1989, Dallas, Tex., November 1989, which is incorporated herein by reference.
It is known that a signal quality estimate, often the signal-to-noise ratio, is needed when using different diversity receivers. In diversity reception the most common diversity receivers combine the signals before or after detection and comprise e.g. selective combining, maximal-ratio combining and equal-gain combining. The diversity signals are usually detected using a Viterbi detector, the signals being combined after detection. However, it is preferable to combine the signals before detection, thus achieving a greater amplification of the signal. Diversity receivers have been described in greater detail for example in the book William C. Y. Lee: Mobile Communications Engineering, chapter 10, Combining technology, pages 291-336, McGraw-Hill, USA, 1982, which is incorporated herein by reference.
An object of the present invention is to implement a method for estimating the interference strength directly from a received signal without the help of ML detection and simultaneously enabling the combination of diversity signals before detection when using diversity receivers.
This is achieved with the method set forth in the preamble characterized in that a reference signal is generated from the estimated channel impulse response and the predetermined sequence by convolution; an interference strength connected to the desired signal is generated using the differences of the reference signal and the predetermined sequence received from the channel; a strength value of the desired signal is generated, whereby a quality estimate is generated by dividing the strength value of the desired signal by the interference strength of the desired signal; and diversity combining is performed in such a manner that the symbols of the different branches corresponding with each other in the time domain are combined, and the outputs of the matched filters of each branch and the autocorrelation taps of the impulse response are weighted with the quality estimate of each branch.
The receiver of the invention is characterized in that the receiver comprises reference signal means for generating a reference signal from the estimated channel impulse response and the predetermined sequence by convolution; interference means for generating the interference strength associated with the desired signal using the differences of the reference signal and the predetermined sequence received from the channel; the receiver is arranged to generate a strength value of the desired signal and quality means are arranged to generate a quality estimate by dividing the strength value of the desired signal by the interference strength of the desired signal; and combining means of the diversity branches combine the symbols of the different branches corresponding to each other in the time domain, and that the receiver is arranged to weight the matched filter outputs of each branch and the autocorrelation taps of the impulse response with the quality estimate of each branch.
Great advantages are achieved with the invention. With the method of the invention the interference strength can be estimated directly from the received signal without performing a Viterbi detection. By avoiding the use of the Viterbi algorithm usually applied to the ML method memory and time used for calculating are saved. The generated interference strength can be utilized for estimating the status of the channel, as help in methods of estimating bad frames and for scaling the ML metric. Furthermore, the interference strength can be utilized for diversity combining and it is particularly useful when multipath signals are combined before detection.
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Jokinen Harri
Raitola Mika
Ranta Pekka
Altera Law Group LLC
Nokia Telecommunications Oy
Pham Chi
Tran Khanh Cong
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