Multisensor reception method for a fixed base station of a communications network exchanging data with mobile stations and device for its implementation

Claim 1

A method enabling the improvement of the multisensor reception of a radiocommunications system exchanging signals between at least one fixed base station providing for multisensor reception by means of a network of sensors and processing of the signals, by computing a channel-formation weighting vector W at reception in a transparent manner seen from the base station, wherein said weighting vector W is an eigen vector corresponding to a maximum eigen value of a matrix R xx of one of the signals received by said network of sensors, said computing the weighting vector W comprising the steps of: acquiring a vector (X(n)) corresponding to a signal received by the network of sensors, after sampling at a determined frequency; estimating said weighting vector W according to an algorithm of the gradient made adaptive by the updating, at each new sample, of the pitch μ of the computation of the gradient, the pitch μ being determined to limit the losses as a function of the signal-to-noise ratio; standardizing the estimated vector W to ensure a modulus equal to 1 according to a criterion of maximazation; and filtering data elements by means of the weighting vector W.

Claim 2

A method enabling the improvement of the multisensor reception of a radiocommunications system exchanging signals between at least one fixed base station providing for multisensor reception by means of a network of sensors and processing of the signals, by computing a channel-formation weighting vector W at reception in a transparent manner seen from the base station, wherein said weighting vector W is an eigen vector corresponding to a maximum eigen value of a matrix R xx of one of the signals received by said network of sensors, said computing the weighting vector W comprising the steps of: acquiring a vector (X(n)) corresponding to a signal received by the network of sensors, after sampling at a determined frequency; estimating said weighting vector W according to an algorithm of the gradient made adaptive by the updating, at each new sample, of the pitch μ of the computation of the gradient, the pitch μ being determined to limit the losses as a function of the signal-to-noise ratio; standardizing the estimated vector W to ensure a modulus equal to 1 according to a criterion of maximazation; and filtering data elements by means of the weighting vector W.

Claim 3

A method enabling the improvement of the multisensor reception of a radiocommunications system exchanging signals between at least one fixed base station providing for multisensor reception by means of a network of sensors, wherein at least two sensors are reference sensors, and processing of the signals, comprising the steps of: acquiring a vector (X(n)) corresponding to one of the signals received by said network at a determined sampling frequency; computing vectors of intercorrelation of a signal (X(xn)) received by the network of sensors and said signals received respectively for the reference sensors, the computation being updated at each new sample; selecting that reference sensor, that has a highest power value with a difference greater than a determined threshold; computing a weighting vector (W(n)) by taking the ratio between an intercorrelation vector corresponding to a selected sensor and the power of a signal received by this sensor; and filtering the data elements by means of the weighting vector W.

Claim 4

A method enabling the improvement of the multisensor reception of a radiocommunications system exchanging signals between at least one fixed base station providing for multisensor reception by means of a network of sensors, wherein at least two sensors are reference sensors, and processing of the signals, comprising the steps of: acquiring a vector (X(n)) corresponding to one of the signals received by said network at a determined sampling frequency; computing vectors of intercorrelation of a signal (X(xn)) received by the network of sensors and said signals received respectively for the reference sensors, the computation being updated at each new sample; selecting that reference sensor, that has a highest power value with a difference greater than a determined threshold; computing a weighting vector (W(n)) by taking the ratio between an intercorrelation vector corresponding to a selected sensor and the power of a signal received by this sensor; and filtering the data elements by means of the weighting vector W.