Graph signal processing based pilot pattern design and channel estimation for OFDM system - Bin HE; Guobing LI; Yuan CHEN; Guomei ZHANG (物联网学报)
Orthogonal frequency division multiplexing (OFDM) is one of the key technologies in the physical layer of the internet of things (IoT).Pilot design and channel estimation are key issues in OFDM systems.In view of the problem of performance loss by fixed pilot pattern due to the complexity and variety of IoT communication scenarios, a pilot design and channel estimation scheme based on graph signal processing (GSP) was proposed.Firstly, the time-frequency resource block was modeled as a graph signal, and the channel estimation problem was reformulated into a sampling and reconstruction problem of the graph signal.Then, considering the influence of time-frequency fading, a weighted graph adjacency matrix was designed to construct a graph topology structure based on the time-frequency position.On this basis, the pilot position is selected based on the graph signal sampling theory, a greedy pilot pattern design algorithm based on weighted graph topology was proposed.At the same time, signal reconstruction was performed based on the graph signal reconstruction method, and a channel estimation method based on the graph smoothness constraint was proposed.Compared with the conventional scheme, simulation results show that the proposed method achieves higher channel estimation accuracy in high-speed scenarios of double selective channels, and effectively reduces pilot overhead in low-speed scenarios.