Method and Arrangement for Improved Model Order Selection

A method of enabling model order selection for joint channel synchronization and noise covariance estimation of at least one received signal in a wireless communication network, said method comprising the steps of:

• generating a spatially and temporally stacked signal model by stacking successive samples of temporally adjacent received signal vectors and corresponding training vectors;
• computing a noise variance matrix for each hypothesized synchronization position, channel length and stacking order, based on the stacked training symbols;
• and
• determining a best synchronization position for the received signal, based on the stacked training vectors;
• wherein said determining step comprises jointly determining the best synchronization position for the received signal and estimating a channel length and a stacking order for said signal model based on the stacked training vectors.

A receiver arrangement configured for enabling model order selection for joint channel synchronization and noise covariance estimation of at least one received signal in a wireless communication network, said receiver arrangement comprising:

• a stacking circuit configured for generating a spatially and temporally stacked signal model by stacking successive samples of temporally adjacent received signal vectors and corresponding training vectors;
• a noise variance estimation circuit configured for computing a noise variance matrices for all hypothesized synchronization positions, channel lengths and stacking orders, based on the stacked training symbols;
• a synchronization determining circuit configured for determining a best synchronization position for the received signal, based on the stacked training vectors;
• and
• wherein said synchronization determining circuit is configured for jointly determining the best synchronization position for the received signal and estimating a channel length and a stacking order for said signal model based on the stacked training vectors.