SAGE (Space-alternating Generalized Expectation-maximization) based channel estimation method in CoMP multi-user system

Abstract

The invention discloses an SAGE (Space-alternating Generalized Expectation-maximization) based a channel estimation method in a CoMP multi-user system, which mainly solves the problem that in a cooperative multi-point transmission CoMP multi-user system, a combined channel estimation computing method has high complexity. The method comprises the following steps: initialization and iterated initial value computing; CIR (Channel Impulse Response) estimation value iteration processing: determining the collection of selected users and collection of non-selected users of a k-th iteration, and performance of interference cancellation, CIR estimation value update, received signal reconstruction on the selected users, wherein CIR estimation values and received signal construction values of all the users in the connection of the non-selected users to a base station maintain to be same as those of a last iteration; and performance of outputting the CIR estimation values of M users to the base station. In the invention, on the base that the mean-square error property of the channel estimation is ensured, the complexity of the multi-user combined channel estimation is reduced. The method disclosed by the invention can be used for the channel estimation of the CoMP multi-user system in a wireless communication field.

Description

technical field [0001] The invention belongs to the technical field of mobile communication, and relates to a channel estimation method based on generalized alternating maximum SAGE, which can be used for estimating the channel impulse response CIR of a coordinated multi-point transmission CoMP multi-user system. Background technique [0002] The CoMP technology is a key technology adopted in the advanced Long Term Evolution LTE-A system. Based on the different degrees of sharing of link channel state information and user data information by each coordinated base station, CoMP technology transforms the original interference between adjacent cells into known useful information, effectively solving the problem of cell edge interference, Improved cell edge throughput and system throughput. On the other hand, in order to improve the capacity of the uplink system, the advanced Long-Term Evolution LTE-A adopts the multi-user multiple-input multiple-output MU-MIMO technology, and ...

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Problems solved by technology

See literature: Yongzhe Xie, Costas.N.Georghiades, "Two EM-type channel estimation Algorithms for OFDM with transmitter diversity", IEEE transactions on communications, 2003. This method only gives the least squares LS for multi-antenna systems Channel estimation scheme, and because the LS algorithm itself does not consider noise, it cannot obtain good MSE performance

In order to improve the performance of channel estimation, another maximum a posteriori probability MAP channel estimation method based on generalized alternating maximum SAGE is proposed. The algorithm transforms the minimum mean square error MMSE channel estimation problem of multiple antennas into the maximum posterior probability For the problem of empirical probability MAP estimation, see the literature: Gao J, "Low-complexity map channel estimation for mobile MIMO-OFDM systems", IEEE transactions on communications, Vol.7, NO.3, Mar.2008. The application environment of this method It is still a single-user multi-antenna system. At the same time, this method does not take into account that the update sequence of the channel impulse response CIR in the SAGE algorithm will affect its convergence performance.

Therefore, the SAGE-based LS algorithm and the SAGE-based MAP estimation method in the above single-user multi-antenna system are not suitable for direct application to CoMP multi-user systems

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