In this letter, we propose two low complexity algorithms for least square (LS) and minimum mean square error (MMSE) based multi-cell joint channel estimation (MJCE). The algorithm for LS-MJCE achieves the same complexity and mean square error (MSE) performance as the previously proposed most efficient algorithm, while the algorithm for MMSE-MJCE is superior to the conventional ones, in terms of either complexity or MSE performance.

In this letter, a low complexity multi-cell joint channel estimation (MJCE) scheme is proposed. With proper arrangement of the multi-cell midamble matrix and channel impulse response (CIR) vector, the MJCE operation is formulated to solve a block-Toeplitz linear system. The block-Levinson algorithm is adopted to solve this problem instead of the Cholesky algorithm. Our results show that the proposed MJCE scheme can be a practical choice with significantly lower complexity, compared with the previous schemes with the Cholesky algorithm.

In this paper, a multi-cell joint channel estimation (JCE) method is proposed for the TD-SCDMA downlink. In the proposed multi-cell JCE approach, the received midambles from adjacent cells are jointly processed, rather than being treated as interference as in single cell channel estimation. By jointly processing all the received midambles, the user can simultaneously estimate the channel impulse responses (CIRs) for both its home cell and adjacent cells. If the received signal from adjacent cells has a delay, multi-cell JCE is still operable with slight adjustment in the midamble matrix, and the performance loss is also minor. The performance of multi-cell JCE is analyzed and evaluated by simulations. The results demonstrate that the proposed multi-cell JCE method can significantly improve the channel estimation accuracy. When the signal from each cell has similar power level, the mean square error (MSE) of the estimated CIRs for all cells is lower than 0.01. With more accurate CIRs from multi-cell JCE, multi-cell JD also yields better performance compared with the single cell channel estimation methods.