LAUSR

In this paper, we show a novel algorithm for strong line-of-sight (LoS) multiple-input-multiple-output (MIMO) channel equalization. With optimally spaced antennas under specific arrangements, the LoS channels can be made spatially orthogonal. In practice, antenna displacements are expected. Conventional algorithms like zero-forcing (ZF) do not consider the special properties of the LoS MIMO channel and result in high complexity. We show that the LoS MIMO channel can be factorized into a product of three matrices. Thereby, the two diagonal matrices at the outer product positions are the most varying terms and should be compensated dynamically. Being a good tradeoff between complexity and robustness, the proposed sequential channel equalization is applied in a reverse order of the factorization. The algorithm can be applied to LoS MIMO systems with uniform linear or rectangular arrays, which are making use of digital or analog equalization. By considering the usage of the Winograd butterfly and Butler matrices, the number of multiplications in both digital and analog implementations of the proposed solution is increasing approximately linearly with respect to the number of antennas, while the complexity of the state-of-the-art designs grows quadratically. As found numerically and verified experimentally, the proposed method performs nearly as well as the ZF-based algorithms with near-optimal arrangements, while having significantly lower complexity.