Semi-blind Channel Estimation For Multiuser MIMO-CDMA System Based On Subsapce Projection

In order to get greater performance, it is necessary to estimate the wireless channel parameters accurately. The channel estimation methods can be classified into three kinds: the channel estimation method based on training data, blind channel estimation method and semi-blind channel estimation method. The channel estimation method based on training data is simple, but has low bandwidth efficiency. Blind channel estimation method has better bandwidth efficiency, but is more complexity. Semi-blind channel estimation method has the advantage of non-blind channel estimation method and blind channel estimation method. Therefore, it is clear that bandwidth efficiency, algorithmic complexity and the estimation accuracy are three key difficulties need to be solved.In this paper, we propose a semi-blind channel estimation approach based on vector space projections. We have studied two channel estimation methods and analyze their advantages and disadvantages. Then, we propose a wireless communication system in which the techniques of multiple-input multiple-output(MIMO), code division multiple access(CDMA) and orthogonal space-time block codes(OSTBC) are integrated together for the purpose of achieving high data rate. For this system, we propose a semi-blind channel estimation approach based on vector space projections. We demonstrate that such composite channel information vector(CCI) belongs to two non-orthogonal subspaces and can be computed blindly in a single step using the vector space projection(VSP) method. In order to reduce the computation complexity, we propose an equivalent but computationally effective single-step solution. Additionally, only one training block is required to overcome the problem of sign ambiguity. Numerical results demonstrate that, in addition to improving the bandwidth efficiency, the proposed method offers better performance in terms of channel estimation accuracy and bit-error-rate(BER) as compared with the standard non-blind least-squares channel estimation approach.The main innovation points of this paper can be summarized as follows:(1)We propose an equivalent but computationally effective single-step solution in which the channel estimation amounts to searching for the principal eigenvector of a certain matrix with moderate size.(2)We demonstrate how a composite channel information(CCI) vector can be formed at the receiver end of a multiuser MIMO-CDMA system with OSTBC. Using the vector space projections(VSP) method, this CCI vector can be viewed as the intersection of these two subspaces and thus can be computed by alternative projections. So we do not need to estimate more parameters.