Two Methods for Decreasing the Computational Complexity of the MIMO ML Decoder
Takayuki Fukatani, Ryutaroh Matsumoto, Tomohoko Uyematsu
Abstract
We propose use of QR factorization with sort and Dijkstra's algorithm for decreasing the computational complexity of the sphere decoder that is used for ML detection of signals on the multi-antenna fading channel. QR factorization with sort decreases the complexity of searching part of the decoder with small increase in the complexity required for preprocessing part of the decoder. Dijkstra's algorithm decreases the complexity of searching part of the decoder with increase in the storage complexity. The computer simulation demonstrates that the complexity of the decoder is reduced by the proposed methods significantly.
Create a lesson
Related papers
Optimal Communication for Distributed Sparse Histogram Aggregation
Fangwei Ye, Yijun Fan
Hardware-Efficient Reinforcement-Learned Scheduling for Quantum LDPC Decoders
Mohsen Moradi, Vahid Nourozi, Wei Tang et al.
Making Every Edit Count: Efficient Binary Edit Correction at the Gilbert-Varshamov Bound
Ryan Gabrys, Shubhransh Singhvi, Eitan Yaakobi
Timely Ground-Station Status Delivery via UAV-Assisted Data Collection and Hierarchical RL
Xiangjian Gao, Mohammad Moltafet, Hamid R. Sadjadpour
Uniform Sampling of Linear Codes with Prescribed Hull Dimension
Keita Ishizuka
Quantum Private Information Retrieval on Forests
Mohamed Nomeir, Sennur Ulukus