In radio apparatus, e.g. digital cellular mobile phones, the encoding and decoding methods employed have been widely studied. In reception pulsed signal interferences create problems which makes a received signal difficult to process by methods known in the art. The problems related to pulsed interferences has in the past been studied e.g. in an article by K. R. Matis, J. W. Modestino: Performance of Selected Coded Direct-Sequence Receiver Structures in Pulsed Interference, Milcom 1985, vol. 3, Boston, Mass. In said article the principle of interference measurement is described, but there is no mention of how to implement said measurement. In the reference it is also not mentioned how an AGC signal can be made to comply with the level of a utility information signal included in a received signal.
Decoding methods have also been studied by means of simulation, and the main results thereof are published in the following references: (1) J. Juntti: Performance Simulations of a Convolutionally Coded DS Systems in Pulsed Noise Interference, Licenciate's Dissertation, University of Oulu, Department of Electricity, May 1990, and (2) K. Jyrkka: Performance Simulations of a Convolutionally Coded DS System in Pulsed CW Interference, Diploma study, University of Oulu, Department of Electricity, November 1990. Said references give no suggestions for solution of how the AGC signal could in practice be made to conform ideally to the level of the information signal.
In conventional receivers the decoding operation can be carried out e.g. by means of a circuit arrangement like the one shown in FIG. 1. The radio frequency circuits 2 of a receiver process, i.e. amplify and convert, the signals received from an antenna 1 so that they can be processed in a demodulator circuit 3. The result of the demodulation is conducted to an integrator 4, from the output of which samples are taken at symbol time intervals T. The samples are conducted further to a quantization circuit 6. The processing of the frames of the received digital signal, i.e. deinterleaving, is carried out in circuit 7, and the output thereof is conducted to a decoder circuit 8, from the output of which the utility data 9 contained in the signal received with the antenna 1 is provided.
As mentioned above, after demodulation the received signal is conducted to a quantization circuit 6. In the quantization circuit 6 the received signal is quantized into three or more levels (soft decision quantization) instead of using two level quantization (hard decision quantization). In such soft decision quantization, reliability information is added to every symbol decision. The reliability information can be presented, for example, as shown in FIG. 2, where 8 quantization levels are used. There are two numbers showing the reliability information for each quantization interval. These numbers are called metrics and they are determined separately when the received signal is compared with both of the symbols. The metrics are used in decoding algorithms.
An optimal convolution decoder is used to minimize error probability in a long symbol sequence. The error probability of a sequence will be minimized when such a sequence is selected so that a so called Euclidjan distance is minimized compared to the received symbol sequence. The optimal decoder calculates the Euclidean distance for each received sequence of all possible transmitted sequences. The calculation of the Euclidean distances is done by adding, after every symbol decision (soft decision), a metric corresponding to the Euclidean distance of each sequence. Usually the distances are calculated using the Viterbi algorithm
Optimum values for the metrics can be calculated, when the quantization levels are fixed and if the statistical properties of interfering signals are known. It is known in the art to optimize metrics in AWGN (Additive White Guassian Noise) channels. However, when pulse interference occurs in such a channel, the metrics calculated at above can no longer be optimal. Again, if the statistical properties of the pulse interference are known it is possible to calculate the optimal metric values, but usually in communication systems the properties of the interference signal are not known a priori. The optimal receiver should measure the interference and then analyse the statistical properties of the interference. To avoid these difficulties in receiver realisation, the metrics of the AWGN-channel are usually used. A drawback is that the performance is degraded considerably when pulse interferences occur in the channel, the metrics can no longer be optimal unless changed to conform with the noise strength.
In the Finnish patent application no. 923738 filed simultaneously with the corresponding Finnish patent application to this application, the formation of an AGC control signal is presented optimally using median filtering with which the AGC control signal ideally conforms with the level of the information signal.