Abstract
Multiple-input multiple-output (MIMO) techniques are significantly advanced in contemporary high-rate wireless communications. The computational complexity and bit-error-rate (BER) performance are main issues in MIMO systems. An algorithm is proposed based on a traditional K-Best algorithm, coupling with the fast QR decomposition algorithm with an optimal detection order for the channel decomposition, the Schnorr–Euchner strategy for solving the zero floating-point and sorting all the branches’ partial Euclidean distance, the sphere decoding algorithm for reducing the search space. The improved K-Best algorithm proposed in this paper has the following characteristics: (i) The searching space for the closest point to a region is smaller compared to that of the traditional K-Best algorithm in each dimension; (ii) it can eliminate the survival candidates at early stages, and (iii) it obtains better performance in the BER and the computational complexity.
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Yang, Jl. (2019). On an Improved K-Best Algorithm with High Performance and Low Complexity for MIMO Systems. In: Panigrahi, B., Trivedi, M., Mishra, K., Tiwari, S., Singh, P. (eds) Smart Innovations in Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 670. Springer, Singapore. https://doi.org/10.1007/978-981-10-8971-8_28
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DOI: https://doi.org/10.1007/978-981-10-8971-8_28
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