Abstract:

High-frequency(HF) communication is a communication technology which relies on the reflection of radio waves in the Ionosphere to achieve ultra-long distance transmission.HF communication also plays an irreplaceable role to guarantee the communication accessibility.However,the HF channel exhibits severe multi-path delay spread and Doppler extension,and therefore demonstrates a typical feature of time-frequency doubly-selective fading.These channel features will bring severe challenges to the reliability of HF communication.Consequently,channel equalization algorithms should be adopted at the receiver to detect the transmitted data.Conventional equalization algorithms for HF channels commonly encounter the problem of slow convergence,so that they cannot adapt to the complicated HF channel characteristics.On the other hand,the fast-converging equalization algorithms suffer from excessively high computational complexity,which fails to meet the need of engineering implementation.To address these aforementioned problems,a low-complexity orthogonal approximate message passing(OAMP) equalization algorithm is proposed for the HF doubly-selective fading channel.Specifically,we propose a LU decomposition-based iterative triangular matrix solution,and exploit the sparseness feature of the HF channel matrix.In this way,the complexity of the matrix inversion operation can be effectively reduced,and the amount of computations can be further lowered in the original OAMP equalization algorithm.Simulation results show that the proposed low-complexity OAMP algorithm demonstrates the same bit-error rate(BER) performance as the original one,while the computational complexity can be reduced by approximately 88%.

Key words: high-frequency communications, doubly-selective fading channel, low complexity equalization